Evolución, sistemas evolutivos, enfoque lingüístico, lingüística matemática, reconocimiento sintáctico de patrones, inferencia gramatical, gramáticas evolutivas, computación evolutiva, programación genética, matrices evolutivas, redes neuronales evolutivas, reconocimiento de patrones, autómatas celulares evolutivos, sistemas complejos, sistemas expertos, aprendizaje de maquinas, procesos de Markov, recursividad, complejidad, informática, sistemas adaptativos, hardware evolutivo.

 

Crecimiento, aprendizaje, pensamiento, transformación de nuestra imagen de la realidad, inteligencia artificial, vida artificial, procesos de descomposición, el desarrollo y transformación de las empresas, sociedades, organizaciones, países, galaxias y universos, vida, cambio.

 

Evolución y Educación, Invención por evolución, Sistemas Evolutivos y música, Robótica evolutiva, sistemas evolutivos de la naturaleza, generación de paisajes, árboles, nubes, ríos, etc.

 

 

www.fgalindosoria.com/eac/

Evolution and Evolutionary Systems

LINKS  to EVOLUTION

 

Evolución y Sistemas Evolutivos

LIGAS a   EVOLUCIÓN

http://www.fgalindosoria.com/eac/evolucion/links/Evolution.htm

 

Fernando Galindo Soria

www.fgalindosoria.com             fgalindo@ipn.mx

Red de Desarrollo Informatico REDI   www.LaRedi.com

 

 

Creación de la página  www    Cd. De México a  2 de Junio del 2001

Últimas actualizaciones  27 de Mayo del 2007, 9 de Diciembre del 2008, 9 de Julio del 2009, 11 de Julio del 2010

 

 

Ir a

Evolución y Sistemas Evolutivos, Sistemas Afectivos y Sistemas Concientes

 

Evolución y Sistemas Evolutivos           Sistemas Afectivos             Sistemas Concientes

Matrices Evolutivas y Dinámica Dimensional

 

 

 

Go to   Evolution and Evolutionary Systems      /      Ir a   Evolución y Sistemas Evolutivos

Go to   Principal Page       /       Ir a   Página Principal

 

Go to   Links Pages         /        Ir a   Páginas de Ligas

 

FGS Papers     /     Artículos de FGS

Papers     /     Artículos

Thesis over Evolutionary Systems     /     Trabajos de titulación sobre sistemas evolutivos

Pages of peoples and organizations over Evolutionary Systems     /     Páginas de personas y organizaciones sobre sistemas evolutivos

Complementary Bibliography over Evolutionary Systems     /     Bibliografía complementaria sobre sistemas evolutivos

 

Evolution     /     Evolución

History of evolutionary thought     /     Historia del Pensamiento Evolutivo

Approaches, Methods and Tools     /     Enfoques, Métodos y Herramientas

Applications     /     Aplicaciones

Book´s     /     Libros

Events     /     Eventos

Others link over Evolutionary Systems     /     Otras ligas sobre sistemas evolutivos

 

 

 

LINKS  /  LIGAS

EVOLUTION  /  EVOLUCIÓN

 

 

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Naui Ollin el que al girar y repetirse cíclicamente genera la evolución

 

Cencahua es la palabra Nahuatl utilizada para describir evolución, y significa movimiento que tiende a la unidad

 

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EVOLUTION  /  EVOLUCIÓN

 

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Evolution  /  Evolución

 

Evolución

Fernando Galindo Soria, 20 de Septiembre de 1995

Teoría y Práctica de los Sistemas Evolutivos Versión b, Ciudad de México 1997, Editor  Jesús M. Olivares Ceja.

“...se plantea en esencia que la evolución, el crecimiento, la vida, el aprendizaje, el pensamiento, la transformación de nuestra imagen de la realidad, los procesos de descomposición, el desarrollo y transformación de las empresas, sociedades, organizaciones, países, galaxias y universos, etc., son manifestaciones de un mismo proceso general de transformación o cambio, y que existen  reglas y propiedades generales que se aplican a las diferentes manifestaciones particulares.

Por facilidad al concepto general lo denominaremos Evolución, aunque lo podríamos llamar de muchas otras formas, como cambio o transformación. O sea que, cuando nos refiramos a la evolución no nos estaremos refiriendo al concepto particular que tiene asociado, sino al concepto general con el cual integra y representa a todas las manifestaciones particulares.”

http://www.fgalindosoria.com/eac/evolucion/evolucion/evolucion.htm

 

 

La más bella historia jamás contada

Hubert Reeves

“...desde hace quince mil millones de años acontece una misma aventura que une el universo, la vida y el hombre como los capítulos de una larga epopeya. Hay una misma evolución, del Big Bang a la inteligencia, que empuja en el sentido de una creciente complejidad: las primeras partículas, los átomos, las moléculas, las estrellas, las células, los organismos, los seres vivientes, hasta estos curiosos animales que somos nosotros... Todo se sucede en una misma cadena, a todos les arrastra un mismo movimiento.” (FGS, Link July 4, 2010)

http://www.sisabianovenia.com/LoLeido/NoFiccion/ReevesBella.htm

 

 

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Complexity and Evolution  / Complejidad y Evolución.

 

 

Cosmic Evolution: The Rise of Complexity in Nature

Cubierta delanteraEric J. Chaisson

Harvard University Press, 2002 - 288 páginas

“We are connected to distant space and time not only by our imaginations but also through a common cosmic heritage. Emerging now from modern science is a unified scenario of the cosmos, including ourselves as sentient beings, based on the time-honored concept of change. From galaxies to snowflakes, from stars and planets to life itself, we are beginning to identify an underlying ubiquitous pattern penetrating the fabric of all the natural sciences--a sweepingly encompassing view of the order and structure of every known class of object in our richly endowed universe.” (FGS, Link July 4, 2010)

http://books.google.com.mx/books?id=KG2SZouhFuIC&dq=cosmic+evolution+chaisson&source=gbs_navlinks_s

 

Cosmic Evolution: The Rise of Complexity in Nature

Eric J. Chaisson

Harvard University Press, 2002 - 288 páginas

 

 

Cosmic Evolution: The Rise of Complexity in Nature [Paperback]

Eric J. Chaisson (Author) (FGS, Link July 4, 2010)

http://www.amazon.com/Cosmic-Evolution-Rise-Complexity-Nature/dp/0674009878/ref=sr_1_1?ie=UTF8&s=books&qid=1262825233&sr=8-1

 

 

Proof that evolution can create complexity

http://www.youtube.com/watch?v=ym4IR_nKGOM&feature=related

 

 

Midiendo la Complejidad

Wednesday, January 6, 2010

“Uno de los problemas actuales en el estudio de los sistemas complejos en general y de los Sistemas Adaptativos Complejos en particular, es cómo podemos medirlos, y dado que la medicion de estos sistemas es un requerimiento basico a la hora de comparar sistemas de forma cientifica y de buscar su optimizacion.
Esta es una pregunta abierta, pero existen alternativas que han sido propuestas, la ultima de las cuales lei en el libro "Cosmic Evolution: The Rise of Complexity in Nature. Eric J. Chaisson".
Al presentar la historia de la complejidad el autor intenta probar 2 cosas. Por una parte pretende mostrar que los aumentos en complejidad son compatibles con la segunda ley de termodinamica. La segunda ley, en su interpretacion mecanica-estadistica, requiere que el desorden aumente en un sistema cerrado, lo que implicaría que la complejidad (lo contrario a desoden) debería disminuir. Sin embargo, una estructura compleja como una galaxia, una estrella o un organismo es un sistema abierto, capaz de sustentar complejidad al exportar suficiente desorden a su ambiente, para mas que justificar sus aumentos de complejidad internos. De hecho, la segunda ley se mantiene dado que el desorden si aumenta en el sistema mayor, aquel que consiste de la estructura compleja mas su ambiente circundante. Por ejemplo, el aumento de complejidad en una estrella joven, tiene su balance en el desorden que exporta a su ambiente a traves de la radiacion.
Su segunda meta es demostrar que el fenomeno fisico que produce complejidad es la misma para todas estas transiciones. De forma muy basica el fenomeno que el explica es como sigue: Donde existen fuertes gradientes de energía, a veces las condiciones son correctas para la emergencia espontanea de estructuras que tiendan a disipar estos gradientes. Mientras este gradiente exista, esas estructuras posrán ser estables, mantenidas en un cuasi estado-estable de alta complejidad, esto es lejos de equilibrio en el sentido estadistico-mecanico, por el flujo de energia a traves de ellas.” (FGS, Link July 4, 2010)

http://cas-chile.blogspot.com/2010/01/midiendo-la-complejidad.html

 

 

Complex system

“A complex system is a system composed of interconnected parts that as a whole exhibit one or more properties (behavior among the possible properties) not obvious from the properties of the individual parts. This characteristic of every system is called emergence and is true of any system, not just complex ones.

A system’s complexity may be of one of two forms: disorganized complexity and organized complexity.[2] In essence, disorganized complexity is a matter of a very large number of parts, and organized complexity is a matter of the subject system (quite possibly with only a limited number of parts) exhibiting emergent properties.” (Wikipedia, 5/vii/2010)

http://en.wikipedia.org/wiki/Complex_system

 

Sistema complejo

“Un Sistema Complejo está compuesto por varias partes interconectadas o entrelazadas cuyos vínculos contienen información adicional y oculta al observador. Como resultado de las interacciones entre elementos, surgen propiedades nuevas que no pueden explicarse a partir de las propiedades de los elementos aislados. Dichas propiedades se denominan propiedades emergentes.

El sistema complicado, en contraposición, también está formado por varias partes pero los enlaces entre éstas no añaden información adicional. Nos basta con saber cómo funciona cada una de ellas para entender el sistema. En un sistema complejo, en cambio, existen variables ocultas cuyo desconocimiento nos impide analizar el sistema con precisión. Así pues, un sistema complejo, posee más información que la que da cada parte independientemente. Para describir un sistema complejo hace falta no solo conocer el funcionamiento de las partes sino conocer como se relacionan entre sí.” (Wikipedia, 5/vii/2010)

http://es.wikipedia.org/wiki/Sistemas_complejos

 

Emergence

“In philosophy, systems theory, science, and art, emergence is the way complex systems and patterns arise out of a multiplicity of relatively simple interactions. Emergence is central to the theories of integrative levels and of complex systems.” (Wikipedia, 5/vii/2010)

http://en.wikipedia.org/wiki/Emergence

 

Emergencia (filosofía)

“La emergencia hace referencia a aquellas propiedades o procesos de un sistema no reducibles a las propiedades o procesos de sus partes constituyentes. El concepto de emergencia se relaciona estrechamente con los conceptos de autoorganización y superveniencia y se define en oposición a los conceptos de reduccionismo y dualismo.” (Wikipedia, 5/vii/2010)

http://es.wikipedia.org/wiki/Emergencia_(filosof%C3%ADa)

 

 

Complejidad y Evolución.

Esbozo de la lógica de la complejidad

Carlos Eduardo Maldonado

“TESIS: Pensar en términos de complejidad equivale exactamente a pensar en términos evolutivos.”

http://gemini.udistrital.edu.co/comunidad/grupos/trabajo/complejidad/memorias/primer%20encuentro/DIA%204/02.%20CARLOS%20MALDONADO%20-%20COMPLEJIDAD%20Y%20EVOLUCI%d3N.pdf

 

Carlos Eduardo Maldonado

http://www.carlosmaldonado.org/

articulos

http://www.carlosmaldonado.org/articulos/

 

 

Portal de Carlos H. von der Becke

sistema complejo adaptivo

http://www.geocities.com/ohcop/adaptivo.html

 

 

Sistemas Adaptativos Complejos

Complex Adaptive Systems -CAS "..donde una inteligencia global emerge de interacciones locales de seres individualmente no inteligentes." -Sociobiology, O.E.Wilson-

http://cas-chile.blogspot.com/

 

 

Epistemología de la Complejidad

Juan Machín, Santiago, Chile, 25 de Enero de 2007

www.pastoraldedrogadiccion.cl/docs2007/intro_epistem.ppt

 

 

Temas Complejidad Generales

http://www.denisenajmanovich.com.ar/htmls/0700_links/ver_links.php?id_categoria=2

 

 

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Information, Energy, and Evolution

Mark Burgin, Department of Mathematics, University of California, Los Angeles, and Irving Simon

“Abstract: Within the current theory of evolution, the development in the direction of higher

complexity is taken to be a necessary condition. This gives birth to a problem why this direction is prevalent for evolution. Philosophers and scientists tried to substantiate this condition and to explain it, yet the question still remains open. Our aim is to find specific regularities in nature that make complexity the chosen direction. Three main causes for this direction are deduced from initial principles, assuming that information and energy are the vital nutrients for evolution. Consequently, we base our explication and explanation of causes on the principles of information theory, Ashby’s principle of requisite variety/complexity, as well as we suggest and ground some additional principles of the system development. This makes possible to separate three principal stages for evolution of living organisms: biological, neurological, and epistemological.”

http://cogprints.org/2359/1/EvoInf.pdf

 

 

Evolving self-reference: Matter, symbols, and semantic closure

by Howard H. Pattee (1995)

“Abstract:

A theory of emergent or open-ended evolution that is consistent with the epistemological foundations of physical theory and the logic of self-reference requires complementary descriptions of the material and symbolic aspects of events. The matter-symbol complementarity is explained in terms of the logic of self-replication, and physical distinction of laws and initial conditions. Physical laws and natural selection are complementary models of events. Physical laws describe those invariant events over which organisms have no control. Evolution by natural selection is a theory of how organisms increase their control over events. A necessary semantic closure relation is defined relating the material and symbolic aspects of organisms capable of open-ended evolution.

http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.17.6467&rep=rep1&type=pdf

http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.17.6467

 

 

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Biological evolution  /  Evolución biológica

 

Evolution

Evolution is the change in the inherited traits of a population of organisms through successive generations. After a population splits into smaller groups, these groups evolve independently and may eventually diversify into new species. A nested hierarchy of anatomical and genetic similarities, geographical distribution of similar species and the fossil record indicate that all organisms are descended from a common ancestor through a long series of these divergent events, stretching back in a tree of life that has grown over the 3,500 million years of life on Earth. To distinguish biological evolution from other senses of the term "evolution" used outside of the field of biology – such as cultural evolution, technological evolution and the evolution of language – it is sometimes referred to as genetic evolution or organic evolution” (Wikipedia, 26/vi/2010)

http://en.wikipedia.org/wiki/Evolution

 

Evolución biológica

“La evolución biológica es el conjunto de transformaciones o cambios a través del tiempo que ha originado la diversidad de formas de vida que existen sobre la Tierra a partir de un antepasado común.[3] La palabra evolución para describir tales cambios fue aplicada por vez primera en el siglo XVIII por el suizo Charles Bonnet en su obra "Consideration sur les corps organisés". No obstante, el concepto de que la vida en la Tierra evolucionó a partir de un ancestro común ya había sido formulada por varios filósofos griegos,[6] y la hipótesis de que las especies se transforman continuamente fue postulada por numerosos científicos de los siglos XVIII y XIX, a los cuales Charles Darwin citó en el primer capítulo de su libro El origen de las especies.” (Wikipedia, 26/vi/2010)

http://es.wikipedia.org/wiki/Evoluci%C3%B3n_biol%C3%B3gica

 

 

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Evolución Artículos

http://www.iieh.com/index.php/evolucion

 

 

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Evolutionary developmental biology

(evolution of development or informally, evo-devo)

 

Evolutionary developmental biology

Evolutionary developmental biology (evolution of development or informally, evo-devo) is a field of biology that compares the developmental processes of different animals and plants in an attempt to determine the ancestral relationship between organisms and how developmental processes evolved. It addresses the origin and evolution of embryonic development; how modifications of development and developmental processes lead to the production of novel features, such as the evolution of feathers[1]; the role of developmental plasticity in evolution; how ecology impacts in development and evolutionary change; and the developmental basis of homoplasy and homology.” (Wikipedia, 5/vii/2010)

http://en.wikipedia.org/wiki/Evolutionary_developmental_biology

 

 

evo-devo  Biología evolutiva del desarrollo

 

Biología evolutiva del desarrollo

“La biología evolutiva del desarrollo (o informalmente evo-devo, del inglés evolutionary developmental biology) es un campo de la biología que compara el proceso de desarrollo de diferentes organismos con el fin de determinar sus relaciones filogenéticas.[1] De igual forma, Evo-Devo, busca identificar los mecanismos del desarrollo que dan origen a cambios evolutivos en los Fenotipos de los individuos (Hall, 2003). El interés principal de esta nueva aproximación evolutiva es entender cómo la forma orgánica (estructuras novedosas y nuevos patrones morfológicos) evoluciona. De este modo, la evolución se define como el cambio en los procesos de desarrollo.” (Wikipedia, 5/vii/2010)

http://es.wikipedia.org/wiki/Biolog%C3%ADa_evolutiva_del_desarrollo

 

Pere Alberch

“Pere Alberch Vie (Badalona, 2 de noviembre de 1954- 13 de marzo de 1998) Biólogo teórico del desarrollo y embriólogo experimental. Su carrera científica se dedicó principalmente a problemas de morfogénesis durante la evolución (filogenia) y desarrollo embrionario (ontogenia).” (Wikipedia, 5/vii/2010)

http://es.wikipedia.org/wiki/Pere_Alberch

 

 

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Evolving Hierarchical Systems

 

Evolving Hierarchical Systems (Hardcover)

by Stanley N. Salthe

Publisher: Columbia University Press, Hardcover: 343 pages (September 30, 1985)

http://www.amazon.com/Evolving-Hierarchical-Systems-Stanley-Salthe/dp/0231060165

 

Product Description
”A bold effort to find a functional and transactional framework for synthetic evolutionary theory, "Evolving Hierarchical Systems" seeks to represent the order in nature by discriminating a hierarchical system and defining the logical boundaries of the concepts inherent in this system (such as time, causality, complexity, partitioning, scale, and polarity). Salthe's basic assumption is that the world is unlimitedly complex. Biology and some other sciences, such as geology and applied physics, have become entangled in this complexity with, the author writes, 'as little ability to negotiate it as a fly in a spider's web'. He argues that biological nature in particular is undercharacterized in our representations, and because of that so is the rest of nature. The book first describes the principles of hierarchical structure and discusses the process of discovering the relevant aspects of the hierarchy of nature.It then brings in the concept of self-reference and moves onto an interpretation and explanation of organic evolution in this framework. While Salthe's focus is in biology, the outline of a hierarchy theory he presents is asserted to be a 'philosophical machine' that can be applied as a hermeneutical tool to many fields of inquiry concerned with change in complex systems. Felt by the author to also be a response to Jacques Monod's "Chance and Necessity", this book is a significant statement on the hierarchical organization of the surface of the earth. It is provocative reading not only for biologists but also for anthropologists, sociologists, geologists, and scientists interested in general systems research.”

 

 

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Signalling theory

 

Signalling theory

“Within evolutionary biology, signalling theory refers to a body of theoretical work examining communication between individuals. The central question is when animals with conflicting interests should be expected to communicate "honestly". Mathematical models in which organisms signal their condition to other individuals as part of an evolutionarily stable strategy are the principal form of research in this field.” (Wikipedia December 20, 2008)

http://en.wikipedia.org/wiki/Signalling_theory

 

Evolutionarily stable strategy  ESS  (Sometimes but grammatically incorrectly evolutionary stable strategy)

“In game theory and behavioural ecology, an evolutionarily stable strategy (ESS) is a strategy which, if adopted by a population of players, cannot be invaded by any alternative strategy that is initially rare. An ESS is an equilibrium refinement of the Nash equilibrium -- it is a Nash equilibrium which is "evolutionarily" stable meaning that once it is fixed in a population, natural selection alone is sufficient to prevent alternative (mutant) strategies from successfully invading.

The ESS was developed in order to define a class of solutions to game theoretic problems, equivalent to the Nash equilibrium, but which could be applied to the evolution of social behaviour in animals. Nash equilibria may sometimes exist due to the application of rational foresight, which would be inappropriate in an evolutionary context. Teleological forces such as rational foresight cannot explain the outcomes of trial-and-error processes, such as evolution, and thus have no place in biological applications. The definition of an ESS excludes such Nash equilibria.” (Wikipedia December 20, 2008)

http://en.wikipedia.org/wiki/Evolutionarily_stable_strategy

 

Estrategia evolutivamente estable

“En teoría de juegos, una estrategia evolutivamente estable (o EEE) es una estrategia que, si es adoptada por una población, no puede ser invadida por ninguna otra estrategia alternativa. El concepto es un refinamiento del equilibrio de Nash. La diferencia entre un equilibrio de Nash y una EEE es que un equilibrio de Nash puede existir a veces por la suposición de que la previsión racional evita que los jugadores utilicen una estrategia alternativa sin costes a corto plazo, pero que finalmente será vencida por una tercera estrategia. Una EEE está definida de manera que se excluyen tales equilibrios, y asume solo que la selección natural evita que los jugadores utilicen estrategias que lleven a recompensas menores.

La definición de EEE fue introducida por John Maynard Smith y George R. Price en 1973 (para una explicación más detallada, véase el libro de Maynard Smith Evolution and the Theory of Games de 1982) basándose en el concepto de William Donald Hamilton (1967) de estrategia imbatible en la proporción de sexos. La idea puede remontarse a Ronald Fisher (1930) y Charles Darwin (1859).” (Wikipedia, 20 de Diciembre del 2008)

http://es.wikipedia.org/wiki/Estrategia_evolutivamente_estable

 

 

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Computational phylogenetics and Cladistics

 

Computational phylogenetics

Computational phylogenetics is the application of computational algorithms, methods and programs to phylogenetic analyses. The goal is to assemble a phylogenetic tree representing a hypothesis about the evolutionary ancestry of a set of genes, species, or other taxa. For example, these techniques have been used to explore the family tree of hominid species[1] and the relationships between specific genes shared by many types of organisms.[2] Traditional phylogenetics relies on morphological data obtained by measuring and quantifying the phenotypic properties of representative organisms, while the more recent field of molecular phylogenetics uses nucleotide sequences encoding genes or amino acid sequences encoding proteins as the basis for classification. Many forms of molecular phylogenetics are closely related to and make extensive use of sequence alignment in constructing and refining phylogenetic trees, which are used to classify the evolutionary relationships between homologous genes represented in the genomes of divergent species. The phylogenetic trees constructed by computational methods are unlikely to perfectly reproduce the evolutionary tree that represents the historical relationships between the species being analyzed. The historical species tree may also differ from the historical tree of an individual homologous gene shared by those species.

Producing a phylogenetic tree requires a measure of homology among the characteristics shared by the taxa being compared. In morphological studies, this requires explicit decisions about which physical characteristics to measure and how to use them to encode distinct states corresponding to the input taxa. In molecular studies, a primary problem is in producing a multiple sequence alignment (MSA) between the genes or amino acid sequences of interest. Progressive sequence alignment methods produce a phylogenetic tree by necessity because they incorporate new sequences into the calculated alignment in order of genetic distance. Although a phylogenetic tree can always be constructed from an MSA, phylogenetics methods such as maximum parsimony and maximum likelihood do not require the production of an initial or concurrent MSA.

http://en.wikipedia.org/wiki/Computational_phylogenetics

 

 

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Cladistics

Cladistics (ancient Greek: κλάδος, klados, "branch") is a form of biological systematics which classifies living organisms on the basis of shared ancestry. It can be distinguished from other taxonomic systems, such as phenetics, by its focus on evolutionary relationships; while other systems usually use morphological similarities to group similar species into genera, families and other higher level classification, cladistics tries to construct a tree representing the ancestry of organisms and species. Cladistics is also distinguished by its emphasis on objective, quantitative analysis, rather than subjective decisions that some other taxonomic systems rely upon.

http://en.wikipedia.org/wiki/Cladogram

 

 

Cladograma

Un cladograma es un diagrama representativo en la clasificación biológica taxonómica de los organismos, en el que se muestra la relación entre distintas especies según una característica derivada, resultado del análisis cladístico de una especie. Los cladogramas son importantes herramientas filogenéticas para el estudio de conceptos científicos.

Los cladogramas son similares a los diagramas de huevos, o bien a los genogramas. Sin embargo, éstos últimos contienen información de descendencia directa de individuos, mientras que un cladograma sólo representa una descendencia hipotética, además de ser de varias especies y no de organismos de una sola.

http://es.wikipedia.org/wiki/Cladograma

 

 

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Phylogenetic tree

A phylogenetic tree or evolutionary tree is a tree showing the evolutionary relationships among various biological species or other entities that are believed to have a common ancestor. In a phylogenetic tree, each node with descendants represents the most recent common ancestor of the descendants, and the edge lengths in some trees correspond to time estimates. Each node is called a taxonomic unit. Internal nodes are generally called hypothetical taxonomic units (HTUs) as they cannot be directly observed.

http://en.wikipedia.org/wiki/Phylogenetic_trees

 

 

Árbol filogenético

Un árbol filogenético es un árbol que muestra las relaciones de evolución entre varias especies u otras entidades que se cree que tuvieron una descendencia común. Un árbol filogenético es una forma de cladograma.

http://es.wikipedia.org/wiki/%C3%81rbol_filogen%C3%A9tico

 

 

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Robinson-Foulds metric

The Robinson-Foulds metric is a way to measure the distance between phylogenetic trees. It is defined as (A + B)/2 where A is the number of leaf splits implied by the first tree but not the second tree and B is the number of leaf splits implied by the second tree but not the first tree.

Properties: In their 1981 paper Robinson and Foulds proved that the distance is in fact a metric.

Algorithms for computing the metric: In 1985 Day gave an algorithm based on perfect hashing that computes this distance that has only a linear complexity in the number of nodes in the trees. A randomized algorithm that uses hash tables that are not necessarily perfect has been shown to approximate the Robinson-Foulds distance with a bounded error in sublinear time.

Specific applications: The metric has been used to compute distances between phylogenetic trees using the treedist program in the PHYLIP suite. The Robinson-Foulds metric has also been used in quantitative comparative linguistics to compute distances between trees that are supposed to represent how languages are related to each other.

http://en.wikipedia.org/wiki/Robinson-Foulds_metric

 

 

Metrics for Phylogenetic Networks I: Generalizations of the Robinson-Foulds Metric
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Volume 6 , Issue 1 January 2009
Gabriel Cardona, Mercè Llabrés, Francesc Rosselló, Gabriel Valiente

http://portal.acm.org/tipsvc.cfm?id=1512455&sess=%27%2A%5CS%2CRL%5B%2B3%20%20%20%0A

 

 

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Research and Teaching site of Pablo Vinuesa
at the Center for Genomic Sciences
environmental and evolutionary microbiology

http://www.ccg.unam.mx/~vinuesa/

 

Introducción a la Inferencia Filogenética

Pablo Vinuesa

http://www.ccg.unam.mx/~vinuesa/pdf/Minicurso_IBT_PDCBq_20_27Mar09.pdf

 

 

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Substitution matrix

“In bioinformatics and evolutionary biology, a substitution matrix describes the rate at which one character in a sequence changes to other character states over time. Substitution matrices are usually seen in the context of amino acid or DNA sequence alignments, where the similarity between sequences depends on their divergence time and the substitution rates as represented in the matrix.” (Wikipedia December 30, 2009)

http://en.wikipedia.org/wiki/Substitution_matrix

 

Matriz de sustitución

“En biología evolutiva una matriz de sustitución, o de puntuación, describe el ritmo al que un carácter en una secuencia cambia a otro carácter con el tiempo. Las matrices de sustitución se ven usualmente en el contexto de alineamiento de secuencias de aminoácidos o ADN, donde la similitud entre secuencias depende del tiempo desde su divergencia y de los ritmos de sustitución según se representan en la matriz.[1]

1. Altschul, S.F. Amino acid substitutions matrices from an information theoretic perspective. J. Mol. Biol. 219, 555-665 (1991).” (Wikipedia, 30 de Diciembre del 2009)

 http://es.wikipedia.org/wiki/Matriz_de_sustituci%C3%B3n

 

 

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Evolution of the Universe  /  Evolución del Universo

 

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Book

The Life of the Cosmos

Lee Smolin

Oxford University Press US, Jan 1999

Description

“Lee Smolin offers a new theory of the universe that is at once elegant, comprehensive, and radically different from anything proposed before. Smolin posits that a process of self organization like that of biological evolution shapes the universe, as it develops and eventually reproduces through black holes, each of which may result in a new big bang and a new universe. Natural selection may guide the appearance of the laws of physics, favoring those universes which best reproduce. The result would be a cosmology according to which life is a natural consequence of the fundamental principles on which the universe has been built, and a science that would give us a picture of the universe in which, as the author writes, "the occurrence of novelty, indeed the perpetual birth of novelty, can be understood.

 

Smolin is one of the leading cosmologists at work today, and he writes with an expertise and force of argument that will command attention throughout the world of physics. But it is the humanity and sharp clarity of his prose that offers access for the layperson to the mind bending space at the forefront of today's physics.” (FGS Link, 26/vii/2010)

http://www.oup.com/us/catalog/general/subject/?view=usa&view=usa&ci=9780195126648&cp=24297

 

 

The Life of the Cosmos

The Life of the Cosmos is a 1997 book by theoretical physicist Lee Smolin. In the book, Smolin details his fecund universes theory which applies the principle of natural selection to the birth of universes. Smolin posits that the collapse of black holes could lead to the creation of a new universe. This daughter universe would have fundamental constants and parameters similar to that of the parent universe though with some changes, providing for both inheritance and mutations as required by natural selection. However, while there is no direct analogue to Darwinian selective pressures, it is theorised that a universe with "unsuccessful" parameters will reach heat death before being able to reproduce, meaning that certain universal parameters become more likely than others.” (Wikipedia 26/vii/2010)

http://en.wikipedia.org/wiki/The_Life_of_the_Cosmos

 

 

Fecund universes

“The fecund universes theory (also called cosmological natural selection theory) of cosmology advanced by Lee Smolin suggests that a process analogous to biological natural selection applies at the grandest scales. Smolin summarized the idea in a book aimed at a lay audience called The Life of the Cosmos.

The theory surmises that a collapsing black hole causes the emergence of a new universe on the "other side", whose fundamental constant parameters (speed of light, Planck length and so forth) may differ slightly from those of the universe where the black hole collapsed. Each universe therefore gives rise to as many new universes as it has black holes. Thus the theory contains the evolutionary ideas of "reproduction" and "mutation" of universes, but has no direct analogue of natural selection. However, given any universe that can produce black holes that successfully spawn new universes, it is possible that some number of those universes will reach heat death with unsuccessful parameters. So, in a sense, fecundity cosmological natural selection is one where universes could die off before successfully reproducing, just as any biological being can die without having offspring.” (Wikipedia 26/vii/2010)

http://en.wikipedia.org/wiki/Lee_Smolin#Fecund_universes

 

 

Teoría de los universos fecundos

“La teoría de los universos fecundos, también llamada selección natural cosmológica, es una teoría del físico Lee Smolin, que aplica criterios semejantes a los de la selección natural darwiniana a la cosmología, de suerte que el universo conocido podría ser el resultado de una evolución y una mutación de universos anteriores.[1]

Esta teoría se expone en el libro "The life of the cosmos" (La vida del cosmos), publicado en 1997 por la Oxford Universitiy Press.” (Wikipedia 26/vii/2010) []

http://es.wikipedia.org/wiki/Teor%C3%ADa_de_los_universos_fecundos

 

 

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Andrei Dmitriyevich Linde

Desarrollo la teoría de un universo que se reproduce a si mismo

 

The Self-Reproducing Inflationary Universe

Recent versions of the inflationary scenario describe the universe as a self-generating fractal that sprouts other inflationary universes

by Andrei Linde

SCIENTIFIC AMERICAN November 1994, pag. 48-55

(FGS Link, 26/vii/2010)

http://www.stanford.edu/~alinde/1032226.pdf

 

 

Andrei Linde

“Andrei Linde was born in Moscow on 2 March 1948. He studied physics in the Moscow State University and was a graduate student at the Lebedev Physical Institute, Moscow. In 1972-1974 he together with David Kirzhnits developed a theory of cosmological phase transitions, which was the subject of his PhD. In 1975 he started his work at the Lebedev Physical Institute, and in 1985 he became a Professor of Physics there. In 1989 he joined the Theory Division at CERN, Switzerland, and in 1990 he became a Professor of Physics at Stanford University.

Andrei Linde is one of the authors of the inflationary universe scenario, which is gradually becoming the standard paradigm of modern cosmology, replacing the previous versions of the Big Bang theory. In 1974 he pointed out that the energy density of a scalar field plays the role of the vacuum energy density (cosmological constant) in the Einstein equations. In 1976-1978 he demonstrated that the energy released during the cosmological phase transitions may be sufficient to heat up the universe. These observations became the basic ingredients of the inflationary scenario proposed by Alan Guth in 1981. In 1982 Andrei Linde suggested the new inflationary universe scenario, which resolved the problems of the original model proposed by Guth, while preserving most of its important features. In 1983 he proposed the chaotic inflationary universe scenario, which became the prototype for the new generation of inflationary models. Published in 1986, his theory of an eternal chaotic inflation suggests that our universe is one of many inflationary universes that sprout from an eternal cosmic tree. In this scenario, the universe becomes the multiverse consisting of infinitely many universes of all possible types. The model of hybrid inflation, which he developed in 1991-1994, became one of the most popular inflationary models in the context of supergravity and string cosmology. In 2003 he together with Kachru, Kallosh and Trivedi developed the first mechanism of vacuum stabilization in string theory. It serves as a basis for most of the recent attempts to construct realistic models of elementary particle physics, inflationary cosmology, and the theory of dark energy based on string theory. At present he continues his work on inflation, creation of matter in the universe, the theory of the inflationary multiverse, and the cosmological consequences of string theory.

Andrei Linde works at Stanford University together with his wife, Professor Renata Kallosh. He has two sons, Dimitri and Alexander. He is an author of more than 230 papers on particle physics, phase transitions and cosmology. He has written two books on inflationary cosmology: "Inflation and Quantum Cosmology" and "Particle Physics and Inflationary Cosmology". In 1978 he was awarded the Lomonosov prize of the Academy of Sciences of the USSR for the theory of the cosmological phase transitions. In 2001 he was awarded the Oskar Klein medal in physics by the University of Stockholm. In 2002 he was awarded the Dirac medal by ICTP, Italy. In 2004 he was awarded the Peter Gruber Prize. In 2005 he was awarded the Robinson Prize for Cosmology by the Newcastle University, UK. In 2006 he received the medal of the Institute of Astrophysics in Paris, France for the development of inflationary cosmology. In 2008 he was elected as a member of the National Academy of Sciences of the USA, and appointed the Harald Trap Friis Professor in Physics at Stanford University.” (FGS Link, 26/vii/2010)

http://www.stanford.edu/~alinde/cv.html

 

 

“…A Brief History of the Multiverse

The idea of an inflationary multiverse (the universe consisting of many universes with different properties) was first proposed in 1982 in my Cambridge University preprint Nonsingular Regenerating Inflationary Universe . A more detailed discussion of this possibility was contained in my paper The New Inflationary Universe Scenario published in the book "The Very Early Universe," ed. G.W. Gibbons, S.W. Hawking and S.Siklos, Cambridge University Press, 1983, pp. 205-249…” (FGS Link, 26/vii/2010)

http://www.stanford.edu/~alinde/

 

 

Linde's Key Idea

Linde is best known for proposing "eternal chaotic inflation" to explain a number of problems in cosmology. This variant of cosmic inflation proposes that the false vacuum is eternally inflating in exponential growth powered by repulsive constant random zero point dark energy of negative pressure. This false vacuum is like supersaturated steam in which liquid bubbles of more stable vacuum form with Higgs-Goldstone fields that describe the cohering of most of the pre-inflationary random dark energy into the smooth fabric of curved spacetime. Our universe is only a small causal part of a single bubble, and there are an infinity of bubbles. In fact, there are an infinity of universes like ours on a single bubble which is more like an expanding infinite sheet than a finite spherical surface (suppressing 1 space dimension for ease of visualization).” (Wikipedia 26/vii/2010)

http://en.wikipedia.org/wiki/Andrei_Linde

 

La idea básica de Linde

Según el concepto de "inflación caótica eterna", el falso vacío se esta inflando eternamente en un crecimiento exponencial alimentado por una energía oscura (dark energy) repulsiva constante de naturaleza aleatoria y punto nulo con presión negativa.

Este falso vacío es muy probablemente vapor supersaturado con gotas de líquido de formas de vacío más estable con campos Higgs-Goldstone que describen la coherencia de la mayoría de la energía oscura aleatoria preinflacionaria en la constitución suave del espaciotiempo curvado. Nuestro universo es solo una pequeña parte causal de una única burbuja. Existe un número infinito de burbujas y de hecho existe un número infinito de universos como el nuestro en una burbuja en particular,...” (Wikipedia 26/vii/2010)

http://es.wikipedia.org/wiki/Andrei_Linde

 

 

Structure formation

Structure formation refers to a fundamental problem in physical cosmology. The universe, as is now known from observations of the cosmic microwave background radiation, began in a hot, dense, nearly uniform state approximately 13.7 Gyr ago. However, looking in the sky today, we see structures on all scales, from stars and planets to galaxies and, on much larger scales still, galaxy clusters, and enormous voids between galaxies. How did all of this come about from the nearly uniform early universe?” (Wikipedia, 26/vi/2010)

http://en.wikipedia.org/wiki/Structure_formation

 

Formación de estructuras

“La Formación de estructuras se refiere a un problema fundamental en cosmología física. El Universo, como se conoce actualmente a partir de las observaciones de la radiación de fondo de microondas, empezó en un estado caliente, denso y casi uniforme hace 13700 millones de años. Sin embargo, mirando el cielo actual, vemos estructuras a todas las escalas, desde estrellas y planetas hasta galaxias y a escalas mucho mayores, agrupaciones galácticas y enormes vacíos entre galaxias. ¿Cómo se ha formado todas estas estructuras a partir del uniforme Universo primigenio?” (Wikipedia, 26/vi/2010)

http://es.wikipedia.org/wiki/Formaci%C3%B3n_de_estructuras

 

 

Galaxy formation and evolution

“The study of galaxy formation and evolution is concerned with the processes that formed a heterogeneous universe from a homogeneous beginning, the formation of the first galaxies, the way galaxies change over time, and the processes that have generated the variety of structures observed in nearby galaxies. It is one of the most active research areas in astrophysics.

Galaxy formation is hypothesized to occur, from structure formation theories, as a result of tiny quantum fluctuations in the aftermath of the Big Bang. The simplest model for this that is in general agreement with observed phenomena is the Λ Cold Dark Matter cosmology; that is to say that clustering and merging is how galaxies gain in mass, and can also determine their shape and structure.” (Wikipedia, 26/vi/2010)

http://en.wikipedia.org/wiki/Galaxy_formation_and_evolution

 

Formación y evolución de las galaxias

“La formación de galaxias es una de las áreas de investigación más activas de la astrofísica, y en cierto sentido, esto también se aplica a la evolución de las galaxias. Sin embargo, hay algunas ideas que ya están ampliamente aceptadas.

Lo que se piensa actualmente que la formación de galaxias procede directamente de las teorías de formación de estructuras, formadas como resultado de las débiles fluctuaciones cuánticas en el despertar del Big Bang. Las simulaciones de N-cuerpos también han podido predecir los tipos de estructuras, las morfologías y la distribución de galaxias que observamos hoy en nuestro Universo actual y, examinando las galaxias distantes, en el Universo primigenio.” (Wikipedia, 26/vi/2010)

http://es.wikipedia.org/wiki/Formaci%C3%B3n_y_evoluci%C3%B3n_de_las_galaxias

 

 

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Organization Evolution  /  Evolución de las Organizaciones

 

Ciclo de Nolan

 

1 1 Tecnologías de la información en las organizaciones

11.2 El ciclo de Nolan: una explicación epidémica para la incorporación de TI en la organización

http://pis.unicauca.edu.co/moodle/file.php/24/Recursos_2da_JF/Cap11.pdf

 

 

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Evolutionary Linguistics  /  Lingüística Evolutiva

 

Evolutionary linguistics

Evolutionary linguistics is the scientific study of the origins and development of language. The main challenge in this research is the lack of empirical data: spoken language leaves practically no traces. This led to an abandonment of the field for more than a century. Since the late 1980s, the field has been revived in the wake of progress made in the related fields of psycholinguistics, neurolinguistics, evolutionary anthropology and cognitive science.” (Wikipedia, 26/vi/2010)

http://en.wikipedia.org/wiki/Evolutionary_linguistics

 

Evolutionary linguistics  History

August Schleicher (1821–1868) and his Stammbaumtheorie are often quoted as the starting point of evolutionary linguistics. Inspired by the natural sciences, especially biology, Schleicher was the first to compare languages to evolving species. He introduced the representation of language families as an evolutionary tree in articles published in 1853. Joseph Jastrow published a gestural theory of the evolution of language in the seventh volume of Science, 1886.

The Stammbaumtheorie proved to be very productive for comparative linguistics, but didn't solve the major problem of evolutionary linguistics: the lack of fossil records. The question of the origin of language was abandoned as unsolvable. Famously, the Société Linguistique de Paris in 1866 refused to admit any further papers on the subject.

The field has re-appeared in 1988 in the Linguistic Bibliography, as a subfield of psycholinguistics. In 1990, Steven Pinker and Paul Bloom published their paper "Natural Language & Natural Selection" which strongly argued for an adaptationist approach to language origins. Their paper is often credited with reviving the interest in evolutionary linguistics. This development was further strengthened by the establishment (in 1996) of a series of conferences on the Evolution of Language (now known as "Evolang"), promoting a scientific, multidisciplinary approach to the issue, and interest from major academic publishers (e.g., the Studies in the Evolution of Language series has been appearing with Oxford University Press since 2001) and scientific journals.” (Wikipedia, 26/vi/2010)

http://en.wikipedia.org/wiki/Evolutionary_linguistics#History

 

Evolución del lenguaje (Historia)

“La evolución del lenguaje es el campo teórico de la Biolingüística que trata acerca de cómo emergió y evolucionó el lenguaje en la linea evolutiva del ser humano.

El primero en plantear una teoría seria al respecto fue Lord Monboddo, quien en 1773 publicó The Origin and Progress of Man and Language (El origen y progreso del hombre y el lenguaje), obra de gran erudición en la que explicaba el surgimiento del lenguaje humano a partir las ventajas evolutivas que confirió el mismo: concluía que el lenguaje se desarrolló como un método de supervivencia ventajoso cuando una comunicación clara podía ser determinante para evitar peligros, explicando además las principales características de los idiomas primitivos. En dicha obra, Monboddo emplea argumentos antropológicos y lingüísticos que dejan entrever claramente su compresión y aceptación de mecanismos análogos a la selección natural de Darwin, en el que podría haber influido. Las teorías de Monboddo no fueron muy seguidas, debido sobre todo a las numerosoas excentricidades del lord, que nunca fue tomado muy en serio.

El asunto cayó en un relativo olvido hasta la publicación de El origen de las especies: pocos años después de la publicación de El origen de las especies, el tema se convierte en algo muy polémico. En 1866 la Sociedad Lingüística de París decidió prohibir el tema aludiendo que todas las teorías al respecto eran tan contradictorias entre sí que jamás se podría llegar a un acuerdo. Así, el problema de la evolución del lenguaje quedo suspendido por casi un siglo, siendo luego revivido con la esperanza de que los avances en genética, psicología evolutiva, lingüística y antropología fueran capaces de dar una respuesta.” (Wikipedia, 26/vi/2010)

http://es.wikipedia.org/wiki/Evoluci%C3%B3n_del_lenguaje

 

La evolución de la facultad lingüística

Carlos Muñoz Pérez

Facultad de Filosofía y Letras, UBA

http://cmunozperez.files.wordpress.com/2007/12/la_evolucion_de_la_facultad_linguistica.pdf

 

Language change

Language change or the evolution of language is the phenomenon whereby phonetic, morphological, semantic, syntactic, and other features of language vary over time. All languages change continually. At any given moment the English language, for example, has a huge variety within itself: descriptive linguists call this variety synchronic variation. From these different forms comes the effect on language over time known as diachronic change. Two linguistic disciplines in particular concern themselves with studying language change: historical linguistics and sociolinguistics. Historical linguists examine how people in the past used language and seek to determine how subsequent languages derive from previous ones and relate to one another. Sociolinguists study the origins of language changes and want to explain how society and changes in society influence language.” (Wikipedia, 26/vi/2010)

http://en.wikipedia.org/wiki/Language_change

 

Cambio lingüístico

“Se llama cambio lingüístico al proceso de modificación y transformación que, en su evolución histórica, experimentan todas las lenguas en general, y las unidades lingüísticas de cada uno de sus niveles en particular. El cambio lingüístico se diferencia de la variación lingüística en que en el primero las modificaciones son diacrónicas y, por tanto, las estudia la lingüística histórica, mientras que las variaciones son sincrónicas y la analiza, entre otras disciplinas, la sociolingüística.

Dos factores que han intervenido desde siempre en el cambio lingüístico han sido los préstamos y la analogía, el primer es un ejemplo de causa externa y el segundo de causa interna.

Los cambios lingüísticos se agrupan por conveniencia en tres niveles: el cambio fonético, el cambio morfosintáctico y el cambio léxico-semántico.” (Wikipedia, 26/vi/2010)

http://es.wikipedia.org/wiki/Cambio_ling%C3%BC%C3%ADstico

 

 

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Quantitative comparative linguistics

Quantitative comparative linguistics is a branch of comparative linguistics that applies mathematical models to the problem of classifying language relatedness. This includes the use of computational phylogenetics and cladistics to define an optimal tree (or network) to represent a hypothesis about the evolutionary ancestry and perhaps its language contacts. The probability of relatedness of languages can be quantified and sometimes the proto-languages can be approximately dated.

A goal of comparative historical linguistics is to identify instances of genetic relatedness amongst languages. The steps in quantitative analysis are (i) to devise a procedure based on theoretical grounds, on a particular model or on past experience, etc (ii) to verify the procedure by applying it to some data where there exists a large body of linguistic opinion for comparison (this may lead to a revision of the procedure of stage (i) or at the extreme of its total abandonment) (iii) to apply the procedure to data where linguistic opinions have not yet been produced, have not yet been firmly established or perhaps are even in conflict .

Applying phylogenetic methods to languages is a multi-stage process (a) the encoding stage - getting from real languages to some expression of the relationships between them in the form of numerical or state data, so that those data can then be used as input to phylogenetic methods (b) the representation stage - applying phylogenetic methods to extract from those numerical and/or state data a signal that is converted into some useful form of representation, usually two dimensional graphical ones such as trees or networks, which synthesise and "collapse" what are often highly complex multi dimensional relationships in the signal (c) the interpretation stage - assessing those tree and network representations to extract from them what they actually mean for real languages and their relationships through time.

http://en.wikipedia.org/wiki/Quantitative_comparative_linguistics

 

 

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Evolutionary Game Theory and Linguistic

Typology: a Case Study

Gerhard Jäger

“The paper deals with the typology of the case marking of semantic core roles. The competing economy considerations of hearer (disambiguation) and speaker (minimal effort) are formalized in terms of evolutionary game theory. It will be shown that the case marking patterns that are attested in the languages of the world are those that are evolutionary stable for different relative weightings of speaker economy and hearer economy, given the statistical patterns of language use that were extracted from corpora of naturally occurring conversations.” (FGS Link, 25/vii/2010)

http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.94.8693&rep=rep1&type=pdf

 

Teoría evolutiva de juegos en lingüística

“Recientemente Gerhard Jäger ha aplicado las ideas de la teoría evolutiva de juegos a la lingüística[1] explicando porqué aun habiendo una gran número de posibilidades de marcaje de caso la mayoría de lenguas se decantan entre unos pocos sistemas, probando que en las lenguas con orden básico muy libre la estrategia óptima es un sistema de ergatividad escindida, mientras que en lenguas con un orden de palabra muy rígido el óptimo es el marcaje ocasional del acusativo o la ausencia total de caso, situación que se observa en las lenguas del mundo. Además el esquema de Jäger muestra que las tipologías encontradas en las lenguas del mundo con mayor frecuencia corresponden a equilibrios de Nash de un juego en que tanto el hablante como el oyente tratan de maximizar el entendimiento mutuo.” (Wikipedia 25/vii/2010)

http://es.wikipedia.org/wiki/Teor%C3%ADa_evolutiva_de_juegos#Teor.C3.ADa_evolutiva_de_juegos_en_ling.C3.BC.C3.ADstica

 

 

Grammatical case

“In grammar, the case of a noun or pronoun is a change in form that indicates its grammatical function in a phrase, clause, or sentence. For example, a noun may play the role of subject ("I kicked the ball"), of direct object ("John kicked me"), or of possessor ("My ball"). Languages such as ancient Greek, Latin, and Sanskrit had ways of altering or inflecting nouns to mark roles which are not specially marked in English, such as the ablative case ("John kicked the ball away from the house") and the instrumental case ("John kicked the ball with his foot"). In ancient Greek those last three words would be rendered tō podi (τῷ ποδί), with the noun pous (πούς, foot) changing to podi to reflect the fact that John is using his foot as an instrument (any adjective modifying "foot" would also change case to match). Usually a language is said to "have cases" only if nouns change their form (decline) to reflect their case in this way. Other languages perform the same function in different ways. English, for example, uses prepositions like "of" or "with" in front of a noun to indicate functions which in ancient Greek or Latin would be indicated by changing (declining) the ending of the noun itself.

More formally, case has been defined as "a system of marking dependent nouns for the type of relationship they bear to their heads."[1] Cases should be distinguished from thematic roles such as agent and patient. They are often closely related, and in languages such as Latin several thematic roles have an associated case, but cases are a syntactic notion, while thematic roles are a semantic one. Languages having cases often exhibit free word order, since thematic roles are not dependent on position in a sentence.” (Wikipedia 25/vii/2010)

http://en.wikipedia.org/wiki/Grammatical_case

 

 

Caso (gramática)

“En lingüística moderna, caso es la asignación de un marcaje morfosintáctico a un elemento de la oración según el papel temático que desempeña en la predicción verbal.

En gramática tradicional el término caso sirve para denotar cada una de las diversas formas, según la flexión, de un núcleo de sintagma nominal (sustantivo, adjetivo o pronombre). En cada lengua el mismo caso marca sistemáticamente las mismas relaciones gramaticales.

Caso morfológico y caso sintáctico

El término caso morfológico se refiere a la posibilidad que existe en algunas lenguas de añadir una marca morfológica o distintiva a sustantivos, adjetivos o pronombres según la función sintáctica que estén realizando en la oración. Muchas lenguas, como el español, poseen casos sólo en los pronombres y otras lenguas, como el chino no poseen caso en ningún tipo de palabra.

El caso sintáctico o caso abstracto, por el contrario, es una categoría abstracta postulada por la gramática generativa para todas las lenguas. La teoría del caso explica como el núcleo de todo sintagma nominal recibe una y sólo una interpretación semántico-temática a instancias de un asignador de caso (verbo o preposición), lo cual permite reconocer su función en la oración.” (Wikipedia 25/vii/2010)

http://es.wikipedia.org/wiki/Caso_gramatical

 

 

Morfosintaxis

“La morfosintaxis se refiere al conjunto de elementos y reglas que permiten construir oraciones con sentido y con carentes de ambigüedad mediante el marcaje de relaciones gramaticales, concordancias, indexaciones y estructura jerárquica de constituyentes sintácticos.

Para muchas lenguas el estudio del nivel morfosintáctico puede dividirse en:

·         Morfología lingüística

·         Sintaxis

Sin embargo, para muchas estructuras lingüísticas particulares los fenómenos morfológicos y sintácticos están estrechamente entrelazados y no siempre es posible separarlos. En el caso de las lenguas polisintéticas la distinción es aún más difícil y ni siquiera parece ser posible separar entre morfología y sintaxis, ya que una oración puede estar formada por una única palabra a la que se han añadido un gran número de morfemas. La morfosintaxis da sentido a las oraciones.” (Wikipedia 25/vii/2010)

http://es.wikipedia.org/wiki/Morfosintaxis

 

 

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Creative evolutionary systems / Sistemas Evolutivos creativos

 

Book

Creative evolutionary systems

David Corne, University of Reading, Peter Bentley, University College London, U.K.
Morgan Kaufmann; 1st edition (July 30, 2001)

Kindle Edition, January 15, 2001   

http://ecx.images-amazon.com/images/I/51R3XMCWTBL._SS110_.jpg

Hardcover

$101.00

In Stock.


Description

“The use of evolution for creative problem solving is one of the most exciting and potentially significant areas in computer science today. Evolutionary computation is a way of solving problems, or generating designs, using mechanisms derived from natural evolution. This book concentrates on applying important ideas in evolutionary computation to creative areas, such as art, music, architecture, and design. It shows how human interaction, new representations, and approaches such as open-ended evolution can extend the capabilities of evolutionary computation from optimization of existing solutions to innovation and the generation of entirely new and original solutions.”

 

Contents
”About the Editors Foreword By Margaret Boden Contributors Preface An Introduction to Creative Evolutionary Systems By Peter J. Bentley and David W. Corne Introduction AI and Creativity Evolutionary Computation Creative Evolutionary Systems Is Evolution Creative? PART I - Evolutionary Creativity Chapter 1 - Creativity in Evolution: Individuals, Interactions, and Environments By Tim Taylor 1.1 Introduction 1.2 Creativity and Opened-Ended Evolution 1.3 Design Issues 1.3.1 Von Neumann's Architecture for Self-Reproduction 1.3.2 Tierra 1.3.3 Implicit versus Explicit Encoding 1.3.4 Ability to Perform Other Tasks 1.3.5 Embeddedness in the Arena of Competition and Richness of Interactions 1.3.6 Materiality 1.4 A Full Specification For An Open-Ended Evolutionary Process 1.4.1 Waddington's Paradigm for an Evolutionary Process 1.5 Conclusions Acknowledgments References Chapter 2 - Recognizability of the Idea: The Evolutionary Process of Argenia By Celestino Soddu 2.1 Introduction 2.2 Recognizability, Identity, And Complexity 2.3 Evolutionary Codes: Artificial DNA 2.4 Natural/Artificial Complexity 2.5 Giotto, A Medieval Idea In Evolution 2.6 Rome, Future Scenarios 2.7 Basilica, Generative Software To Design Complexity 2.8 Madrid and Milan, Generated Architecture 2.9 Argen a, The Natural Industrial Object, And The Artificial Uniqueness Of Species 2.10 Argen c Art: Picasso 2.11 Conclusions References Chapter 3 - Breeding Aesthetic Objects: Art and Artificial Evolution By Mitchell Whitelaw 3.1 Introduction 3.2 Breeding Aesthetic Objects 3.2.1 A Case Study?Steven Rooke 3.3 Breeding and Creation 3.3.1 Creative Agency and the Breeding Process 3.3.2 The Evolved Aesthetic Object 3.4 Limits 3.5 Driessens and Verstappen?An Alternative Approach 3.6 Conclusions References Chapter 4 - The Beer Can Theory of Creativity By Liane Gabora 4.1 Introduction 4.2 Culture As An Evolutionary Process 4.2.1 Variation and Convergence in Biology and Culture 4.2.2 Is More Than One Mind Necessary for Ideas to Evolve? 4.2.3 Meme and Variations: A Computer Model of Cultural Evolution 4.2.4 Breadth-First versus Depth-First Exploration 4.2.5 Dampening Arbitrary Associations and Forging Meaningful Ones 4.3 Creativity as The Origin Of Culture 4.3.1 Theoretical Evidence 4.3.2 Archeological Evidence 4.3.3 Evidence from Animal Behavior 4.4 What Caused the Onset of Creativity? 4.5 Conclusions Acknowledgments References PART II Evolutionary Music Chapter 5 - GenJam: Evolution of a Jazz Improviser By John A. Biles 5.1 Introduction 5.2 Overview and Architecture 5.3 Representations 5.4 Genetic Operators and Training 5.4.1 Crossover 5.4.2 Musically Meaningful Mutation 5.5 Real-Time Interaction 5.6 Conclusions References Chapter 6 - On the Origins and Evolution of Music in Virtual Worlds By Eduardo Reck Miranda 6.1 Introduction 6.2 Evolutionary Modeling 6.2.1 Transformation and Selection 6.2.2 Coevolution 6.2.3 Self-organization 6.2.4 Level Formation 6.3 Evolving Sound With Cellular Automata 6.3.1 The Basics of Cellular Automata 6.3.2 The Cellular Automaton Used in Our System 6.3.3 The Synthesis Engine 6.4 Commentary On The Results 6.5 Conclusions Acknowledgments References Chapter 7 - Vox Populi: Evolutionary Computation for Music Evolution By Artemis Moroni, J natas Manzolli, Fernando Von Zuben, and Ricardo Gudwin 7.1 Introduction 7.2 Sound Attributes 7.3 Evolutionary Musical Cycle 7.3.1 The Voices Population 7.3.2 The Rhythm of the Evolution 7.4 Fitness Evaluation 7.4.1 The Consonance Criterion 7.4.2 Melodic Fitness 7.4.3 Harmonic Fitness 7.4.4 Voice Range Criterion 7.4.5 Musical Fitness 7.5 Interface And Parameter Control 7.6 Experiments 7.7 Conclusions Acknowledgments References Chapter 8 - The Sound Gallery?An Interactive A-Life Artwork By Sam Woolf and Adrian Thompson 8.1 Introduction 8.2 Evolvable Hardware 8.2.1 Reconfigurable Chips 8.3 Gallery Setup 8.3.1 Setting 8.3.2 Sensing Systems 8.4 Contextualization: Artificial Life and Art 8.4.1 Evolutionary Algorithms and Visual Arts 8.4.2 Evolutionary Algorithms and Music 8.4.3 Interactive Genetic Art 8.4.4 Interactive, Adaptive, and Autonomous (Nongenetic) Artworks 8.5 The Sound Gallery Algorithms 8.5.1 Two-Phase Hill-Climbing/ Island Model GA 8.5.2 Hill-climbing Phase 8.5.3 Island Model Genetic Algorithm Phase 8.5.4 The Need for Aging 8.5.5 Encoding Scheme 8.5.6 The Fitness Function 8.5.7 galSim 8.6 The Experiment 8.6.1 Results 8.7 Conclusions Acknowledgments References Contents PART III Creative Evolutionary Design Chapter 9 - Creative Design and the Generative Evolutionary Paradigm By John Frazer 9.1 Introduction 9.2 The Adaptive Model From Nature 9.3 The Generative Evolutionary Paradigm 9.4 Problems With The Paradigm 9.5 Concept Seeding Approach 9.6 The Reptile Demonstration 9.7 Universal State Space Modeler 9.8 Logic Fields 9.9 Returning to the Analogy with Nature 9.10 Conclusions References Chapter 10 - Genetic Programming: Biologically Inspired Computation That Exhibits Creativity in Producing Human-Competitive Results By John R. Koza, Forrest H. Bennett III, David Andre, and Martin A. Keane 10.1 Introduction 10.2 Inventiveness And Creativity 10.3 Genetic Programming 10.4 Applying Genetic Programming To Circuit Synthesis 10.4.1 Campbell 1917 Ladder Filter Patent 10.4.2 Zobel 1925 "M-Derived Half Section" Patent 10.4.3 Cauer 1934-1936 Elliptic Filter Patents 10.4.4 Amplifier, Computational, Temperature-Sensing, Voltage Reference, and Other Circuits 10.5 Topology, Sizing, Placement, and Routing Of Circuits Contents 10.6 Automatic Synthesis Of Controllers By Means Of Genetic Programming 10.6.1 Robust Controller for a Two-Lag Plant 10.7 The Illogical Nature Of Creativity And Evolution 10.8 Conclusions References Chapeter 11 - Toward a Symbiotic Coevolutionary Approach to Architecture By Helen Jackson 11.1 Introduction 11.2 Lindenmayer Systems 11.2.1 Example L-Systems 11.2.2 The Isospatial Grid 11.2.3 Spatial Embryology 11.3 Artificial Selection 11.3.1 The Eyeball Test 11.4 Single-Goal Evolution 11.4.1 "Generic Function" as Fitness Function 11.4.2 Evolution toward Low i-Values 11.4.3 Structural Stability 11.4.4 Architecture As a Multigoal Task 11.4.5 Dual-Goal Evolution 11.5 Representation, Systems, And Symbiosis 11.5.1 Coevolution 11.5.2 Na ve Architectural Form Representation 11.5.3 Spatial Embryology 11.6 Conclusions Acknowledgments References Chapter 12 - Using Evolutionary Algorithms to Aid Designers of Architectural Structures By Peter von Buelow 12.1 Introduction 12.2 Analysis Tools Vs. Design Tools 12.3 Advantages Of Evolutionary Systems In Design Contents 12.3.1 Use of Populations 12.3.2 Recombination and Mutation 12.3.3 Wide Search of Design Space 12.3.4 No Knowledge of the Objective Function 12.3.5 Imitation of Human Design Process 12.3.6 Can Learn from Designer 12.4 Characteristics of an IGDT 12.4.1 Definition of the IGDT Concept 12.4.2 Relation of IGDT to Design Process 12.5 Mechanics of an IGDT 12.6 IGDT Operation 12.6.1 Problem Definition 12.6.2 Initial IGDT Generation 12.6.3 Initial Generation with Designer Selection/Interaction 12.6.4 Second-Generation IGDT Response 12.6.5 Second-Generation Designer Interaction 12.6.6 Third Generation 12.7 Conclusions Acknowledgments References PART IV Evolutionary Art Chapter 13 - Eons of Genetically Evolved Algorithmic Images By Steven Rooke 13.1 Introduction 13.2 Using GP for Art 13.2.1 Genetic Variation 13.2.2 Genetic Library 13.2.3 Functions and Node Internals 13.2.4 A Typical Run 13.3 Horizon Lines And Fantasy Landscapes 13.4 Genetic Fractals 13.4.1 Second-Order Subtleties of Orbit Trajectories during Iteration in the Complex Plane 13.5 The Genetic Cross Dissolve 13.6 What Is It? 13.6.1 Constraints of Color and Form 13.6.2 A Joyride for the Visual Cortex? 13.6.3 Approaching the Organic 13.7 Conclusions References Chapter 14 - Art, Robots, and Evolution as a Tool for Creativity By Luigi Pagliarini and Henrik Hautop Lund 14.1 Introduction 14.2 The Social Context Of Electronics 14.2.1 Where Electronics Acts 14.2.2 How Technology Influences Art (the World) 14.2.3 How Technology Gets Feedback (from Art and the World) 14.3 What Artist? 14.3.1 Two Different Concepts or Aspects of the Artist 14.3.2 Art and Human Language: The "Immaterial" Artist 14.3.3 Art and Human Technique: The "Material" Artist 14.4 Electronic Art 14.4.1 A New Electronic Space 14.4.2 The "Material" Electronic Artist 14.4.3 The "Immaterial" Artist and the Uses of Electronics 14.4.4 Example?The Artificial Painter 14.5 Alive Art 14.5.1 Other Artistic Movements Based on Electronics 14.5.2 Alive Art 14.5.3 The Aliver 14.5.4 The "Alive Art Effect" 14.5.5 Example?LEGO Robot Artists 14.6 Conclusions References Chapter 15 - Stepping Stones in the Mist By Paul Brown 15.1 Introduction 15.2 On My Approach as an Artist?A Disclaimer 15.3 Major Influences 15.4 Historical Work?1960s and 1970s 15.5 Early Computer Work 15.6 Recent Work 15.7 Current And Future Directions 15.8 Conclusions Acknowledgments References Chapter 16 - Evolutionary Generation of Faces 409 By Peter J. B. Hancock and Charlie D. Frowd 16.1 Introduction 16.1.1 Eigenfaces 16.1.2 Evolutionary Face Generator System 16.2 Testing 16.2.1 Apparatus 16.2.2 Generation of Face Images 16.2.3 Evolutionary Algorithm 16.2.4 Participants 16.3 Results 16.4 Discussion 16.5 Conclusions Acknowledgments References Chapter 17 - The Escher Evolver: Evolution to the People By A. E. Eiben, R. Nabuurs, and I. Booij 17.1 Introduction 17.2 The Mathematical System Behind Escher's Tiling 17.3 Evolutionary Algorithm Design 17.3.1 Representation 17.3.2 Ground Shape and Transformation System 17.3.3 Genetic Operators: Mutation and Crossover 17.3.4 Selection Mechanism 17.4 Implementation and The Working of The System 17.4.1 Stand-Alone Version 17.4.2 First Networked Version 17.4.3 Second Networked Version 17.5 Conclusions Acknowledgments References PART V Evolutionary Innovation Chapter 18 - The Genetic Algorithm as a Discovery Engine: Strange Circuits and New Principles By Julian F. Miller, Tatiana Kalganova, Natalia Lipnitskaya, and Dominic Job 18.1 Introduction 18.2 The Space of All Representations 18.3 Evolutionary Algorithms That Assemble Electronic Circuits From A Collection of Available Components 18.3.1 Binary Circuit Symbols 18.3.2 Multiple-Valued Circuits 18.4 Results 18.4.1 One-Bit Adder 18.4.2 Two-Bit Adder 18.4.3 Two-Bit Multiplier 18.4.4 Three-Bit Multiplier 18.4.5 Multiple-Valued One-Digit Adder with Carry 18.5 Fingerprinting and Principle Extraction 18.6 Conclusions References Chapter 19 - Discovering Novel Fighter Combat Maneuvers: Simulating Test Pilot Creativity By R. E. Smith, B. A. Dike, B. Ravichandran, A. El-Fallah, and R. K. Mehra 19.1 Introduction 19.2 Fighter Aircraft Maneuvering 19.3 Genetics-Based Machine Learning 19.3.1 Learning Classifier Systems 19.3.2 The LCS Used Here 19.4 "One-Sided Learning" Results 19.5 "Two-Sided Learning" Results 19.6 Differences In Goals And Techniques 19.6.1 Implications of This Goal 19.7 Conclusions Acknowledgments References Chapter 20 - Innovative Antenna Design Using Genetic Algorithms By Derek S. Linden 20.1 Introduction 20.2 Antenna Basics 20.3 Conventional Designs and Unconventional Applications: The Yagi-Uda Antenna 20.4 Unconventional Designs and Conventional Applications: Crooked-Wire And Treelike Genetic Antennas 20.4.1 The Crooked-Wire Genetic Antenna 20.4.2 Treelike Genetic Antennas 20.5 Conclusions References Chapter 21 - Evolutionary Techniques in Physical Robotics By Jordan B. Pollack, Hod Lipson, Sevan Ficici, Pablo Funes, Greg Hornby, and Richard A. Watson 21.1 Introduction 21.2 Coevolution 21.3 Research Thrusts 21.4 Evolution In Simulation 21.5 Buildable Simulation 21.6 Evolution and Construction of Electromechanical Systems 21.7 Embodied Evolution 21.8 Conclusions Acknowledgments References Chapter 22 - Patenting of Novel Molecules Designed via Evolutionary Search By Shail Patel, Ian Stott, Manmohan Bhakoo, and Peter Elliott 22.1 Introduction 22.2 Design Cycle 22.3 Hypothesis: Mechanism Of Action 22.4 Experimental Measures And Modeling Techniques 22.4.1 Molecular Modeling 22.4.2 Neural Networks 22.5 Evolution 22.6 Patent Application 22.6.1 Comparing Patent Spaces 22.7 Conclusions References Index

http://www.elsevier.com/wps/find/bookdescription.cws_home/677950/description#description

 

 

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Evolutionary Art  /  Arte Evolutivo

 

Evolutionary art

Evolutionary art exploits the process of evolution to create an artwork which continually changes according to an evolutionary algorithm.

In common with natural selection and animal husbandry, the members of a population undergoing artificial evolution modify their form or behavior over many reproductive generations in response to a selective regime.

In interactive evolution the selective regime may be applied by the viewer explicitly by selecting individuals which are aesthetically pleasing. Alternatively a selection pressure can be generated implicitly, for example according to the length of time a viewer spends near a piece of evolving art.

Equally, evolution may be employed as a mechanism for generating a dynamic world of adaptive individuals, in which the selection pressure is imposed by the program, and the viewer plays no role in selection, as in the Black Shoals project.” (Wikipedia, 26/vi/2010)

http://en.wikipedia.org/wiki/Evolutionary_art

 

 

Generative art

Generative art refers to art that has been generated, composed, or constructed in an algorithmic manner through the use of systems defined by computer software algorithms, or similar mathematical or mechanical or randomised autonomous processes.

Description

Generative art is a system oriented art practice where the common denominator is the use of systems as a production method. To meet the definition of generative art, an artwork must be self-contained and operate with some degree of autonomy. The workings of systems in generative art might resemble, or rely on, various scientific theories such as Complexity science and Information theory. The systems of generative artworks have many similarities with systems found in various areas of science. Such systems may exhibit order and/or disorder, as well as a varying degree of complexity, making behavioral prediction difficult. However, such systems still contain a defined relationship between cause and effect. Wolfgang Amadeus Mozart's "Musikalisches Würfelspiel" (Musical Dice Game) 1757 is an early example of a generative system based on randomness. The structure was based on an element of order on one hand, and disorder on the other.” (Wikipedia, 26/vi/2010)

http://en.wikipedia.org/wiki/Generative_art

 

Arte generativo

Arte generativo se refiere arte eso se ha generado, se ha compuesto, o se ha construido en algorítmico manera con el uso de los sistemas definidos cerca computadora software algoritmos, o similar matemático o mecánico o seleccionado al azar procesos autónomos.

El arte generativo es una práctica orientada sistema del arte donde está el uso el denominador común de sistemas como método de producción. Para resolver la definición del arte generativo, las ilustraciones deben ser autónomas y funcionar con un cierto grado de autonomía. Los funcionamientos de sistemas en arte generativo pudieron asemejarse, o confían encendido, las varias teorías científicas por ejemplo Ciencia de la complejidad y Teoría de información. Los sistemas de ilustraciones generativas tienen muchas semejanzas con los sistemas encontrados en varias áreas de la ciencia. Tales sistemas pueden exhibir orden y/o desorden, así como un grado que varía de complejidad, haciendo la predicción del comportamiento difícil. Sin embargo, tales sistemas todavía contienen una relación definida entre la causa y el efecto. Wolfgang Amadeus Mozart's “Musikalisches Würfelspiel“(Juego musical de los dados) 1757 es un ejemplo temprano de un sistema generativo basado en aleatoriedad. La estructura fue basada en un elemento de la orden por un lado, y desorden en el otro.”

http://www.worldlingo.com/ma/enwiki/es/Generative_art

 

 

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Roger Alsing Weblog

http://rogeralsing.com/

 

Evolutionary misconceptions

““This is goal oriented evolution, in real life there is no goal”

This is the first misconception, there is no “goal” in the application.
The “source image” is not the goal, it is the ENVIRONMENT in which the organisms live and try to survive.
It is that environment that determines if a specific individual is fit for reproduction or not.
The same way that all other evolution is also dependant on the environment, e.g. in real life the environment is much more complex and dynamic.”

http://rogeralsing.com/2008/12/12/evolutionary-misconceptions/

 

 

Genetic Gallery

http://rogeralsing.com/2008/12/11/genetic-gallery/

 

Fractal mona lisa

http://rogeralsing.com/2008/12/07/genetic-programming-evolution-of-mona-lisa/

 

Evolving Lindenmayer Systems

http://www.cs.ucl.ac.uk/staff/W.Langdon/pfeiffer.html

 

 

Garabatos, programa generador de arte evolutivo.

http://garabatos.wikidot.com/

 

 

 

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Evolutionary Music  /  Música Evolutiva

 


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Sistemas Evolutivos compositores

 

Zanya  Sistema Evolutivo compositor de música

Música y software

http://www.olincuicatl.com/

Índice e introducción

http://www.olincuicatl.com/indiceweb.htm

Contenido

http://www.olincuicatl.com/tesisweb.htm#intromus

 

Prototipo para la harmonización automática de una melodía por computadora

http://mx.geocities.com/tt0317/

 

 

Tecnologías Emergentes incluyendo Música Evolutiva

http://www.wired.com/news/technology/0,1282,59857,00.html

 

 

Desarrollo de un Sistema de Apoyo en la Composición Musical.

Daniel Ignacio Matienzo Iriarte

El sistema analizará las partituras musicales que se introduzcan, creara una matriz evolutiva de ellas composición musical. Se utilizara otra matriz evolutiva para decidir las notas que el sistema acomodara para encontrar las notas con mayor frecuencia y de esta manera también encontrara reglas básicas de al momento de componer su propia música y la mostrara en un pentagrama.

http://www.cs.umss.edu.bo/rep_tesis.jsp?codigo=630&tipo_tes=2

 

 

PCs que crean música de la nada

Autor: David Martín, MuyComputer, Fecha: 24/11/2008

“En la Norwegian University of Science and Technology (NTNU) uno de sus estudiantes de doctorado ha desarrollado un software que es capaz de improvisar canciones y música a partir de la nada, al más puro estilo del género jazz. Oyvind Brandtsegg, el responsable de esta aplicación, es un aficionado a este tipo de música y su "instrumento computerizado" es capaz de tomar sonidos, dividirlos y recombinarlos para crear melodías.”

http://www.muycomputer.com/FrontOffice/ZonaPractica/Especiales/especialDet/_wE9ERk2XxDA0vdjPfH3oxoRM-A7dfAvcoWKnsftGshL83TdjQkLd692LAdZS30Ms

 

 

Sistema de composición musical automática

Aproximaciones Preliminares

Miguel Gómez-Zamalloa Gil

http://gaia.fdi.ucm.es/people/pedro/aad/miguel_zamalloa.pdf

 

 

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Opportunities for Evolutionary Music Composition

Andrew R. Brown, Queensland University of Technology

Australasian Computer Music Conference. Melbourne: ACMA, pp. 27-34.

Abstract

“Traditional compositional techniques and many computer-assisted composition systems have been focused on the production of linear musical products. In an age where non-linear media are increasingly prominent there is a need to reassess these technologies in the light of new opportunities for making music with non-linear outcomes. This paper examines the current state of music making for non-linear media with a particular emphasis on evolutionary music and how and where it might be applied. In addition, some of the implications for computer-based tool design will be outlined.”

(FGS Link, December, 2009)

http://eprints.qut.edu.au/5906/1/5906.pdf

 

 

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Exploiting functional relationships in musical composition

Amy K. Hoover, Kenneth O. Stanley

Evolutionary Complexity Research Group, School of Electrical Engineering and Computer Science, University of Central Florida, Orlando, FL, USA, June 2009

Connection Science , Volume 21 Issue 2-3

Publisher: Taylor & Francis, Inc.

ABSTRACT

“The ability of gifted composers like Mozart to create complex multipart musical compositions with relative ease suggests a highly efficient mechanism for generating multiple parts simultaneously. Computational models of human music composition can potentially shed light on how such rapid creativity is possible. This article proposes such a model based on the idea that the multiple threads of a song are temporal patterns that are functionally related, which means that one instrument's sequence is a function of another's. This idea is implemented in a program called NEAT Drummer that interactively evolves a type of artificial neural network called a compositional pattern-producing network, which represents the functional relationship between the instruments and drums. The main result is that richly textured drum tracks that tightly follow the structure of the original song are easily generated because of their functional relationship to it.”

(FGS Link, January, 2010)

http://portal.acm.org/citation.cfm?id=1552386.1552395&coll=GUIDE&dl=GUIDE&CFID=46014229&CFTOKEN=26545706

 

 

Exploiting Functional Relationships in Musical Composition

Amy K. Hoover and Kenneth O. Stanley

Evolutionary Complexity Research Group, School of Electrical Engineering and Computer Science, University of Central Florida

Connection Science Special Issue on Music, Brain, & Cognition,

Abington, UK: Taylor & Francis, 21:2, 227-251, June 2009.

(FGS Link, January, 2010)

http://eplex.cs.ucf.edu/papers/hoover_connectionscience09.pdf

 

 

The drum tracks in the following 24 MIDI music files were generated by NEAT Drummer and discussed in the Connection Science Special Issue on Music, Brain, & Cognition paper, Exploiting Functional Relationships In Musical Composition.

(FGS Link, July, 2010)

http://eplex.cs.ucf.edu/neatmusic/

 

 

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Evolutionary Complexity (EPlex) Research Group at the University of Central Florida “Welcome to the Evolutionary Complexity (EPlex) Research Group at the University of Central Florida.  Our research focuses on abstracting the essential properties of natural evolution that made it possible to discover astronomically complex structures such as the human brain.  If such properties can be abstracted into computer algorithms, then they can be leveraged to automate the discovery of large-scale neural networks (which is called neuroevolution), robot morphologies, building and vehicle architectures, art, and music.”

(FGS Link, July, 2010)

http://eplex.cs.ucf.edu/

 

 

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Evolving Cellular Automata Music: From Sound Synthesis to Composition

Eduardo Reck Miranda, Sony Computer Science Laboratory Paris

Abstract

“This paper focuses on issues concerning musical composition practices whereby the emergent behaviour of cellular automata is used to model generative processes for synthesised sound and musical forms. We introduce two cellular automata-based systems, Chaosynth and CAMUS, that we have designed for our investigation and discuss their performance and role in the composition of a number of professional pieces of music.

Chaosynth is a granular synthesis system whose parameters are controlled by a variant of a cellular automaton that has been used to model Belousov-Zhabotinskii chemical reactions. CAMUS is a composition system that takes advantage of the pattern propagation properties of cellular automata in order to generate musical forms”

(FGS Link, January, 2010)

http://www.csl.sony.fr/publications/item/?reference=miranda%3A01f

 

 

PDF

http://www.csl.sony.fr/downloads/papers/2001/miranda-almma2001.pdf

 

http://galileo.cincom.unical.it/Music/workshop/articoli/miranda.pdf

 

 

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New challenges for evolutionary music and art

Jon McCormack, Monash University, Australia, April 2006

ACM SIGEVOlution, Volume 1 ,  Issue 1  (April 2006), Pages: 5 – 11, 2006

Publisher: ACM

ABSTRACT

“Art, it was once said, is anything you can get away with. So it is not surprising that evolutionary approaches to music and art research are challenging our notions of what is classified as "Art" and who is the "creator" of this work. The relatively new field of Evolutionary Music and Art (EMA) falls within the spectrum of Evolutionary Computing. If EC is a relatively young discipline, then EMA is even more so, if we consider Richard Dawkins' "Blind Watchmaker" software (1986) as the epoch in this field.1 Dawkins' goal was to demonstrate the power of evolution as a design algorithm, one that could design complexity without the need for an explicit designer. It did not take long for people interested in creativity and aesthetics to grasp the significance of this idea and how it might be used to create a new class of art and design: one that was evolved rather than directly created.”

(FGS Link, July, 2009)

http://portal.acm.org/citation.cfm?id=1138470.1138472&coll=Portal&dl=GUIDE&CFID=45326681&CFTOKEN=72054038

 

Full text available for ACM Digital Library Members:

PdfPdf (326 KB)

http://portal.acm.org/ft_gateway.cfm?id=1138472&type=pdf&coll=Portal&dl=GUIDE&CFID=45326681&CFTOKEN=72054038

 

 

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Life's What You Make: Niche Construction and Evolutionary Art

Jon Mccormack, Oliver Bown, April 2009

Centre for Electronic Media Art, Monash University, Clayton, Victoria, Australia 3800

Lecture Notes In Computer Science; Vol. 5484

Proceedings of the EvoWorkshops 2009 on Applications of Evolutionary Computing: EvoCOMNET, EvoENVIRONMENT, EvoFIN, EvoGAMES, EvoHOT, EvoIASP, EvoINTERACTION, EvoMUSART, EvoNUM, EvoSTOC, EvoTRANSLOG

Section: EvoMUSART Contributions, Pages: 528 – 537, Tübingen, Germany, 2009

Publisher: Springer-Verlag,  Berlin, Heidelberg

ABSTRACT

“This paper advances new methods for ecosystemic approaches to evolutionary music and art. We explore the biological concept of the niche and its role in evolutionary dynamics, applying it to creative computational systems. Using the process of niche construction organisms are able to change and adapt their environment, and potentially that of other species. Constructed niches may become heritable environments for offspring, paralleling the way genes are passed from parent to child. In a creative ecosystem, niche construction can be used by agents to increase the diversity and heterogeneity of their output. We illustrate the usefulness of this technique by applying niche construction to line drawing and music composition.”

(FGS Link, July, 2009)

http://portal.acm.org/citation.cfm?id=1533570.1533637&coll=Portal&dl=GUIDE&CFID=45326681&CFTOKEN=72054038

 

 

Serie del libros Lecture Notes in Computer Science

Editor Springer Berlin / Heidelberg

Libro Applications of Evolutionary Computing

Páginas 528-537

Subject Collection Informática

Fecha de SpringerLink sábado, 11 de abril de 2009

(FGS Link, July, 2009)

http://www.springerlink.com/content/j604803h56337485/

 

 

Life’s What You Make: Niche Construction and Evolutionary Art

Jon McCormack and Oliver Bown

Centre for Electronic Media Art

Monash University, Clayton, Victoria 3800, Australia

(FGS Link, July, 2009)

http://www.csse.monash.edu.au/~jonmc/research/Papers/McCormack_EvoMUSART09.pdf

 

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An evolutionary approach to algorithmic composition

Jontas Manzolli, Interdisciplinary Nucleus of Sound Communication (UNICAMP/NICS), University of Campinas, Rua da Reitoria, 165-13081-970, Campinas SP, Brazil

Artemis Moroni, The Automation Institute (CTI/IA), Technological Center for Informatics, Via Dom Pedro I, KM143/6, Campinas SP, Brazil

Fernando Von Zubens Interdisciplinary Nucleus of Sound Communication (UNICAMP/NICS), University of Campinas, Rua da Reitoria, 165-13081-970, Campinas SP, Brazil

Ricardo Gudwin, The Automation Institute (CTI/IA), Technological Center for Informatics, Via Dom Pedro I, KM143/6, Campinas SP, Brazil

Organised Sound , Volume 4 Issue 2, Pages: 121 - 125

Publisher: Cambridge University Press, June 1999

ABSTRACT

“This paper presents an end-user interface that allows realtime parametric control of sound events resulting in an interactive environment, in which evolutionary computation is applied to algorithmic composition. The resulting system, Vox Populi, uses genetic algorithms to generate and evaluate a sequence of chords played as MIDI data. Harmonic, tonal and voice range fitness are used to control musical features. Based on the ordering of consonance of musical intervals, the notion of approximating a sequence of notes to its harmonically compatible note or tonal centre is used. This method employs fuzzy formalism and is posited as an optimisation approach based on factors relevant to hearing music.

(FGS Link, July, 2009)

http://portal.acm.org/citation.cfm?id=972860.972868&coll=ACM&dl=ACM&CFID=47166338&CFTOKEN=60514033

 

 

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Vox populi: evolutionary for music evolution

Artemis Moroni, Technology Center for Informatics, Brazil

Jonatas Manzolli, Univ. of Campinas, Brazil

Fernando Von Zuben, Univ. of Campinas, Brazil

Ricardo Gudwin, Univ. of Campinas, Brazil

July 2001

Book

Creative evolutionary systems

Section: Evolutionary music, Pages: 205 – 221, 2001

Publisher

Morgan Kaufmann Publishers Inc.  San Francisco, CA, USA

(FGS Link, July, 2009)

http://portal.acm.org/citation.cfm?id=510349.510359&coll=ACM&dl=ACM&CFID=47166338&CFTOKEN=60514033

 

 

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The evolutionary sound synthesis method

Jônatas Manzolli, Adolfo Maia, Jr., Jose Fornari, Furio Damiani

University of Campinas - Unicamp, Brazil, October 2001

International Multimedia Conference; Vol. 9

MULTIMEDIA '01: Proceedings of the ninth ACM international conference on Multimedia, Ottawa, Canada

ABSTRACT

“A mathematical model for interactive sound synthesis based on the application of Genetic Algorithms (GA) is presented. The Evolutionary Sound Synthesis Method (ESSynth) generates sequences of waveform variants by the application of genetic operators on an initial population of waveforms. We describe how the waveforms can be treated as genetic code, the fitness evaluation methodology and how genetic operations such as crossover and mutation are used to produce generations of waveforms. Finally, we discuss the results evaluating the generated sounds.”

(FGS Link, July, 2009)

http://portal.acm.org/citation.cfm?id=500141.500248&coll=ACM&dl=ACM&CFID=47166338&CFTOKEN=60514033

 

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Interactive spatialization and sound design using an evolutionary system

Jose Fornari, Adolfo Maia, Jr, Jônatas Manzolli

Interdisciplinary Nucleus for Sound Studies, Campinas, Brazil

June 2007

NIME '07: Proceedings of the 7th international conference on New interfaces for musical expression

Publisher: ACM

ABSTRACT

We present an interactive sound spatialization and synthesis system based on Interaural Time Difference (ITD) model and Evolutionary Computation. We define a Sonic Localization Field using sound attenuation and ITD azimuth angle parameters and, in order to control an adaptive algorithm, we used pairs of these parameters as Spatial Sound Genotypes (SSG). They are extracted from waveforms which are considered individuals of a Population Set. A user-interface receives input from a generic gesture interface (such as a NIME device) and interprets them as ITD cues. Trajectories provided by these signals are used as Target Sets of an evolutionary algorithm. A Fitness procedure optimizes locally the distance between the Target Set and the SSG pairs. Through a parametric score the user controls dynamic changes in the sound output.

(FGS Link, July, 2009)

http://portal.acm.org/citation.cfm?id=1279740.1279803&coll=ACM&dl=ACM&CFID=47166338&CFTOKEN=60514033

 

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AURAL: evolutionary sonification with robots

 Artemis M.F.S. Moroni, Center for Information Technology Renato Archer, Campinas, Brazil

Jônatas Manzolli, University of Campinas, Campinas, Burkina Faso

March 2009

ACM/IEEE International Conference on Human-Robot Interaction
HRI '09: Proceedings of the 4th ACM/IEEE international conference on Human robot interaction, La Jolla, California, USA,

SESSION: HRI video abstracts, Pages: 199-200, 2009

Publisher: ACM

ABSTRACT

“This study aims to provide a platform for exploring robotic navigation in line with evolutionary computation of sound control data. Real world devices, two mobile robots and an omnidirectional vision system are integrated to sonify trajectories of robots in real time.”

(FGS Link, July, 2009)

http://portal.acm.org/citation.cfm?id=1514095.1514134&coll=ACM&dl=ACM&CFID=47166338&CFTOKEN=60514033

 

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MovMov (2:55 MIN),

http://portal.acm.org/ft_gateway.cfm?id=1514134&type=mov&coll=ACM&dl=ACM&CFID=47166338&CFTOKEN=60514033

 

 

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Frankensteinian Methods for Evolutionary Music Composition

Peter M. Todd, Gregory M. Werner

Book

Musical networks, Pages: 313 – 339, Year of Publication: 1999

Niall Griffith, Peter M. Todd (Eds.). Cambridge, MA, USA MIT Press.

(FGS Link, December, 2009)

http://portal.acm.org/citation.cfm?id=346629

 

Abstract

“Victor Frankenstein sought to create an intelligent being imbued with the rules of civilized human conduct, who could further learn how to behave and possibly even evolve through successive generations into a more perfect form. Modern human composers similarly strive to create intelligent algorithmic music composition systems that can follow prespecified rules, learn appropriate patterns from a collection of melodies, or evolve to produce output more perfectly matched to some aesthetic criteria. Here we review recent efforts aimed at each of these three types of algorithmic composition. We focus particularly on evolutionary methods, and indicate how monstrous many of the results have been. We present a new method that uses coevolution to create linked artificial music critics and music composers, and describe how this method can attach the separate parts of rules, learning, and evolution together into one coherent body.”

PDF

http://www-abc.mpib-berlin.mpg.de/users/ptodd/publications/99evmus/99evmus.doc

 

 

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Autonomous evolutionary music composer

Y. Khalifa, State University of New York, New Paltz, NY

M. Basel Al-Mourad, Aston University, Birmingham, UK

July 2006

GECCO '06: Proceedings of the 8th annual conference on Genetic and evolutionary computation

Publisher: ACM

ABSTRACT

“A second-generation autonomous music composition tool is developed using Genetic Algorithms. The composition is conducted in two Stages. The first Stage generates and identifies musically sound patterns (motifs). In the second Stage, methods to combine different generated motifs and their transpositions are applied. These combinations are evaluated and as a result, musically fit phrases are generated. Four musical phrases are generated at the end of each program run. The generated music pieces will be translated into Guido Music Notation (GMN) and have alternate representation in Musical Instrument Digital Interface (MIDI). The Autonomous Evolutionary Music Composer (AEMC) was able to create interesting pieces of music that were both innovative and musically sound.”

(FGS Link, July, 2009)

http://portal.acm.org/citation.cfm?id=1143997.1144306&coll=ACM&dl=ACM&CFID=47166338&CFTOKEN=60514033

 

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Evolutionary music composer integrating formal grammar

Yaser M. A. Khalifa, Badar K. Khan, Jasmin Begovic, Airrion Wisdom, Andrew Maxymillian Wheeler, State University of New York, New Paltz, NY July 2007

GECCO '07: Proceedings of the 2007 GECCO conference companion on Genetic and evolutionary computation, London, United Kingdom

Publisher: ACM

ABSTRACT

“In this paper, an autonomous music composition tool is developed using Genetic Algorithms. The production is enhanced by integrating formal grammar rules. A formal grammar is a collection of either or both descriptive or prescriptive rules for analyzing or generating sequences of symbols. In music, these symbols are musical parameters such as notes and their attributes. The composition is conducted in two Stages. The first Stage generates and identifies musically sound patterns (motifs). In the second Stage, methods to combine different generated motifs and their transpositions are applied. These combinations are evaluated and as a result, musically fit phrases are generated. Four musical phrases are generated at the end of each program run. The generated music pieces will be translated into Guido Music Notation (GMN) and have alternate representation in Musical Instrument Digital Interface (MIDI). The Autonomous Evolutionary Music Composer (AEMC) was able to create interesting pieces of music that were both innovative and musically sound.”

(FGS Link, July, 2009)

http://portal.acm.org/citation.cfm?id=1274000.1274020&coll=ACM&dl=ACM&CFID=47166338&CFTOKEN=60514033

 

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PDF
http://www.cs.bham.ac.uk/~wbl/biblio/gecco2007/docs/p2519.pdf

 

 

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Genetic algorithms and the abc music notation language for rock music composition

Tomasz Michal Oliwa, The University of Georgia, Athens, GA, USA, July 2008

GECCO '08: Proceedings of the 10th annual conference on Genetic and evolutionary computation, Atlanta, GA, USA

Publisher: ACM

ABSTRACT

“In this paper a music composition system based on genetic algorithms (GAs) will be presented. It can create multi-instrumental, guitar-orientated rock music using objective measures for its fitness functions. The output of this system is a song in the MIDI format. Along with this system, a unique conversion procedure from numerical values to the abc language (and vice versa), which allows the combination of numerical optimization with the rich expressiveness of a music description language, will be shown. The described music composition system will be further compared to other composition systems.”

(FGS Link, July, 2009)

http://portal.acm.org/citation.cfm?id=1389095.1389399&coll=ACM&dl=ACM&CFID=47166338&CFTOKEN=60514033

 

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OMax brothers: a dynamic topology of agents for improvization learning

Gérard Assayag, IRCAM-CNRS UMR Stms, Paris, France

Georges Bloch, University of Strasbourg, Strasbourg France

Marc Chemillier, University of Caen, Caen Cedex France

Arshia Cont, IRCAM-UCSD, Paris, France

Shlomo Dubnov, UCSD, La Jolla, CA

October 2006

AMCMM '06: Proceedings of the 1st ACM workshop on Audio and music computing multimedia, Santa Barbara, California, USA

Publisher:ACM

ABSTRACT

“We describe a multi-agent architecture for an improvization oriented musician-machine interaction system that learns in real time from human performers. The improvization kernel is based on sequence modeling and statistical learning. The working system involves a hybrid architecture using two popular composition/perfomance environments, Max and OpenMusic, that are put to work and communicate together, each one handling the process at a different time/memory scale. The system is capable of processing real-time audio/video as well as MIDI. After discussing the general cognitive background of improvization practices, the statistical modeling tools and the concurrent agent architecture are presented. Finally, a prospective Reinforcement Learning scheme for enhancing the system's realism is described.”

(FGS Link, July, 2009)

http://portal.acm.org/citation.cfm?id=1178723.1178742&coll=ACM&dl=ACM&CFID=47166338&CFTOKEN=60514033

 

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Interactive music composition with the CFE framework

Ying-ping Chen, National Chiao Tung University, Taiwan, April 2007

SIGEVOlution , Volume 2 Issue 1,  (Spring 2007)

Publisher: ACM

ABSTRACT

“This article presents an interactive music composition system which utilizes the black-box optimization model of evolutionary computation. The core CFE framework---Composition, Feedback, and Evolution---is presented and described. The music composition system produces short, manageable pieces of music by interacting with users. The essential features of the system include the capability of creating customized pieces of music based on the user preference and the facilities specifically designed for generating a large amount of music. Finally, several pieces of music composed by the described system are demonstrated as showcases. This work shows that it is feasible and promising for computers to automatically compose customized or personalized music.”

(FGS Link, July, 2009)

http://portal.acm.org/citation.cfm?id=1268573.1268575&coll=ACM&dl=ACM&CFID=46014229&CFTOKEN=26545706

 

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Evolutionary interactive music composition

Tao-yang Fu, Tsu-yu Wu, Chin-te Chen, Kai-chu Wu, Ying-ping Chen

National Chiao Tung University, HsinChu, Taiwan, July 2006

GECCO '06: Proceedings of the 8th annual conference on Genetic and evolutionary computation, Seattle, Washington, USA

Publisher: ACM

ABSTRACT

“This paper proposes the CFE framework---Composition, Feedback, and Evolution---and presents an interactive music composition system. The system composes short, manageable pieces of music by interacting with users. The most important features of the system include creating customized music according to the user preference and providing the facilities specifically designed for producing large amounts of music. We present the structure as well as the implementation of the system and the auxiliary functionalities that enhance the system. We also introduce the auto-feedback test with which we verify and evaluate the interactive music composition system.”

(FGS Link, July, 2009)

http://portal.acm.org/citation.cfm?id=1143997.1144301&coll=ACM&dl=ACM&CFID=46014229&CFTOKEN=26545706

 

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Book

Creative evolutionary systems

Editors

Peter J. Bentley, Univ. College London, London, UK

David W. Corne, Univ. of Reading, Reading, UK

Publisher

Morgan Kaufmann Publishers Inc.  San Francisco, CA, USA

Pages: 576, Year of Publication: 2001

ABSTRACT

“The use of evolution for creative problem solving is one of the most exciting and potentially significant areas in computer science today. Evolutionary computation is a way of solving problems, or generating designs, using mechanisms derived from natural evolution. This book concentrates on applying important ideas in evolutionary computation to creative areas, such as art, music, architecture, and desgn. It shows how human interaction, new representations, and approaches such as open-ended evolution can extend the capabiities of evolutionary computation from optimization of existing solutions to innovation and the generation of entirely new and original solutions. This book takes a fresh look at creativity, exploring what it is and how the actions of evolution can resemble it. Examples of novel evolved solutions are presented in a variety of creative disciplines. The editors have compiled contributions by leading researchers in each discipline.”

(FGS Link, July, 2010)

http://portal.acm.org/citation.cfm?id=510349&coll=ACM&dl=ACM&CFID=47166338&CFTOKEN=60514033

 

 

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Book

The Art of Artificial Evolution: A Handbook on Evolutionary Art and Music

by Juan Romero and Penousal Machado (Editors)

Springer - Natural Computing Series
Hardcover: 458 pages, 169 illus with 91 figs in color edition

November 2007

 “While improvements in computer performance are dramatically changing the computer-generated art industry, scientists in natural computing have teamed up with artists to examine how bioinspired systems can influence art, technology and even aesthetic appreciation.

This comprehensive book gives an up-to-date survey of the relevant bioinspired computing research fields -- such as evolutionary computation, artificial life, swarm intelligence and ant colony algorithms -- and examines applications in art, music and design…”

(FGS Link, July, 2010)

http://art-artificial-evolution.dei.uc.pt/

 

The Art of Artificial Evolution: A Handbook on Evolutionary Art and Music

Summaries

(FGS Link, July, 2010)

http://art-artificial-evolution.dei.uc.pt/abstracts.htm#chap5

 

 

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Speech interfaces from an evolutionary perspective

Clifford Nass, Li Gong, Stanford Univ., Stanford, CA

Communications of the ACM

Volume 43, Number 9 (2000), Pages 36-43

“How does the human brain react when confronted by a talking computer? Answers from psychological research and its design implications help define the limits of what computers should say and how they might say it.”

(FGS Link, December, 2009)

http://portal.acm.org/citation.cfm?id=348941.348976

 

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PDF

http://www-siepr.stanford.edu/programs/SST_Seminars/Evolution_and_Speech.Final1.pdf

 

 

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GenJam (short for Genetic Jammer)

 

GenJam (short for Genetic Jammer) is an interactive genetic algorithm that learns to improvise jazz. It may well be the only evolutionary computation system that is a "working musician." I developed the original version during my sabbatical leave in the 1993-94 academic year and have been extending it ever since. In addition to playing full-chorus improvised solos, GenJam listens to what I play on trumpet and responds interactively when we trade fours or eights. It also engages in collective improvisation, where we both solo simultaneously and GenJam performs a smart echo of my improvisation, delayed by anywhere from a beat to a measure. Finally, it listens to me as I solo and play the "head" of a tune and breeds my measures with its ideas, which steers its solo on a tune in the direction of what I've just played on that tune.”

http://www.ist.rit.edu/~jab/GenJam.html

 

GenJam: Evolutionary Computation Gets a Gig

John A. Biles,

Information Technology Department, RIT

Abstract

“GenJam (short for Genetic Jammer) is an evolutionary computation-based, real-time interactive jazz improvisation agent. GenJam improvises spontaneous autonomous solos and performs interactive and collective improvisation with a human performer by listening to what the human improvises, mapping what it heard to its internal chromosome representation, and using intelligent mutation and crossover operators to develop what the human plays into what it plays in response.

After an overview of GenJam’s architecture in performance settings, this paper describes GenJam’s chromosome structure for representing melodic material, and explains how it interacts in real time with a human performer. Where GenJam gets its musical ideas is discussed next, followed by HCI aspects from both the audience’s and the performer’s perspectives. Finally, a discussion of GenJam as an IT application and a brief prediction of its future conclude the paper.”

http://www.ist.rit.edu/~jab/CITC3/GenJamPaper.pdf

 

 

Evolutionary Computer Music

Book

Miranda, Eduardo Reck; Biles, John Al (Eds.), Springer, 2007

“About this book

The evolutionary computation approach to music is an exciting new development for composers and musicologists alike. For composers, it provides an innovative and natural means for generating musical ideas from a specifiable set of primitive components and processes. For musicologists, these techniques are used to model the cultural transmission and change of a population's body of musical ideas over time. In both cases, musical evolution can be guided by a variety of constraints and tendencies built into the system, such as realistic psychological factors that influence the way music is expressed, experienced, learned, stored, modified, and passed on among individuals.

This book discusses not only the applications of evolutionary computation to music, but also the tools needed to create and study such systems. These tools are drawn in part from research into the origins and evolution of biological organisms, ecologies, and cultural systems on the one hand, and from computer simulation methodologies on the other. They can be combined to create surrogate artificial worlds populated by interacting simulated organisms in which complex musical experiments can be performed that would otherwise be impossible.

This authoritative book, with contributions from experts from around the globe, demonstrates that evolutionary systems can be used to create and to study musical compositions and cultures in ways that have never before been achieved.”

 

Table of contents

“Foreword by David Goldberg.- Preface.- An Introduction to Evolutionary Computing for Musicians.- Evolutionary Computation for Musical Tasks.- Evolution in Digital Audio Technology.- Evolution in Creative Sound Design.- Experiments in Generative Musical Performance with a Genetic Algorithm.- Composing with Genetic Algorithms: GenDash.- Improvising with Genetic Algorithms: GenJam.- Cellular Automata Music: From Sound Synthesis to Musical Forms.- Swarming and Music.- Computational Evolutionary Musicology.”

http://www.springer.com/computer/information+systems/book/978-1-84628-599-8

 

 

Al Biles (John A. Biles)

http://www.ist.rit.edu/~jab/

 

Evolutionary Music Tutorial, GECCO 2005, Al Biles

http://www.ist.rit.edu/~jab/EvoMusic/BilesEvoMusicSlides.pdf

 

Evolutionary Music Bibliography, - Al Biles

to accompany the Evolutionary Music Tutorial given at GECCO 2005

http://www.ist.rit.edu/~jab/EvoMusic/EvoMusBib.html

 

 

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Evolutionary music

Evolutionary music is the audio counterpart to Evolutionary art, whereby algorithmic music is created using an evolutionary algorithm. The process begins with a population of individuals which by some means or other produce audio (e.g. a piece, melody, or loop), which is either initialized randomly or based on human-generated music. Then through the repeated application of computational steps analogous to biological selection, recombination and mutation the aim is for the produced audio to become more musical. Evolutionary sound synthesis is a related technique for generating sounds or synthesizer instruments. Evolutionary music is typically generated using an interactive evolutionary algorithm where the fitness function is the user or audience, as it is difficult to capture the aesthetic qualities of music computationally. However, research into automated measures of musical quality is also active. Evolutionary computation techniques have also been applied to harmonization and accompaniment tasks. The most commonly used evolutionary computation techniques are genetic algorithms and genetic programming.” (Wikipedia, 26/vi/2010)

http://en.wikipedia.org/wiki/Evolutionary_music

 

 

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Musikalisches Würfelspiel

“A Musikalisches Würfelspiel (Musical dice game) was a system for using dice to randomly 'generate' music (long before computer systems). These games were quite popular throughout Western Europe in the 18th century. Several different games were devised, some that did not require dice, but merely 'choosing a random number.' Other famous examples are Johann Philipp Kirnberger's The Ever Ready Composer of Polonaises and Minuets (1757 1st edition; revised 2nd 1783) and Joseph Haydn's Philharmonic Joke (1790).

Mozart's Alleged Musikalisches Würfelspiel

The most well-known was published in 1792, by Mozart's publisher Nikolaus Simrock in Berlin. The game was attributed to Mozart, but this attribution has not been authenticated (Cope 7). The dice rolls randomly selected small sections of music, which would be patched together to create a musical piece. A 'computerised' version of the Musikalisches Würfelspiel making a MIDI file is available here.

Mozart's manuscript K 516f, written in 1787, consisting of numerous two-bar fragments of music, appears to be some kind of game or system for constructing music out of two-bar fragments, but contains no instructions and there is no evidence that dice were involved.” (Wikipedia, 26/vi/2010)

http://en.wikipedia.org/wiki/Musikalisches_W%C3%BCrfelspiel

 

 

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How a computer program became classical music's hot, new composer

'Emily Howell' is a computer program that composes classical music by following rules of music its programmer taught it.

By Matt Rocheleau, / Contributor / June 17, 2010

Christian Science Monitor

“Earlier this year, 6-year-old musical prodigy Emily Howell released an 11-track debut album, resembling the work of history's most renowned classical composers. But instead of receiving the praise given to Beethoven, Mozart, or Bach, the California native has become a lightning rod for controversy within the musical community.

Why? Because Emily is not human.

Emily is a computer program, and "her" ability to write original compositions has called into question whether art is as uniquely human as many like to believe.

"Can computers be creative? In the sense that they are creating something that wasn't there before, yes," says David Cope, Emily's programmer and professor emeritus at the University of California, Santa Cruz. "But so can birds and insects and volcanoes. We have reserved this notion of creativity for humans for a long time, and we are enamored of it."

As he sees it, creativity has never been a human-defining trait. This feeling of his stretches back three decades, to when Mr. Cope first dabbled in teaching music to computers. After hitting a dead end while trying to write new music on his own, Cope created a program called EMI, which he pronounces as "Emmy."

EMI (Experiments in Musical Intelligence) would analyze the work of human composers, pick up on their musical styles, and generate new work seemingly written by the original musician. EMI created "zillions" of compositions before being scrapped for Cope's latest project, he says.

Created in 2003, Emily has only written around 20 songs. It synthesizes its own compositions according to the rules of music that Cope has taught it. And Emily is only fed music that EMI had composed, which gives the new work its own contemporary-classical style.”

http://www.csmonitor.com/Innovation/Tech/2010/0617/How-a-computer-program-became-classical-music-s-hot-new-composer

 

Method Developed to Identify Musical Notes at any Venue

viernes, 23 de abril de 2010 Plataforma SINC

“A team of telecommunications engineers from the University of Jaen (UJA) has created a new method to automatically detect and identify the musical notes in an audio file and generate sheet music. The system identifies the notes even when the type of instrument, musician, type of music or recording studio conditions vary.”

http://www.alphagalileo.org/ViewItem.aspx?ItemId=74333&CultureCode=en

 

 

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Generative music

Generative music is a term popularized by Brian Eno to describe music that is ever-different and changing, and that is created by a system.

·         Theory

o    1.1 Linguistic/Structural

o    1.2 Interactive/Behavioural

o    1.3 Creative/Procedural

o    1.4 Biological/Emergent

(Wikipedia, 26/vi/2010)

http://en.wikipedia.org/wiki/Generative_music

 

Generative music / Linguistic/Structural

“Music composed from analytic theories that are so explicit as to be able to generate structurally coherent material (Loy and Abbott 1985; Cope 1991). This perspective has its roots in the generative grammars of language (Chomsky 1956) and music (Lerdahl and Jackendoff 1983), which generate material with a recursive tree structure.” (Wikipedia, 26/vi/2010)

http://en.wikipedia.org/wiki/Generative_music#Linguistic.2FStructural

 

 

Heinrich Schenker

“Heinrich Schenker (June 19, 1868 - January 13, 1935) was a music theorist, best known for his approach to musical analysis, now usually called Schenkerian analysis.

…Schenker's ideas on analysis were first explored in his Harmony (Harmonielehre, 1906) and Counterpoint (Kontrapunkt, 2 vols., 1910 and 1922), and were developed in the two journals he published, Der Tonwille (1921-24) and Das Meisterwerk in der Musik (1925-30), both of which included content exclusively by Schenker. Schenker regarded his analyses as tools to be used by performers for a deeper understanding of the works they were performing. This is demonstrated by his editions of Ludwig van Beethoven's late piano sonatas, which also include analyses of the works.

In 1932, Schenker published Five Graphic Music Analyses (Fünf Urlinie-Tafeln), analyses of five works using the analytical technique of showing layers of greater and lesser musical detail that now bears his name. Following Schenker's death, his theoretical work Free Composition (Der freie Satz, 1935) was published. It was first translated into English by T. H. Kreuger in 1960 as a dissertation at the University of Iowa; a second translation, by Ernst Oster, was published in 1979.” (Wikipedia, 26/vi/2010)

http://en.wikipedia.org/wiki/Heinrich_Schenker

 

Heinrich Schenker

Heinrich Schenker (19 de junio de 1868 - 13 de enero de 1935) fue un teórico de la música, más conocido por su aproximación al análisis musical, ahora llamado análisis schenkeriano.

Schenker nación en Wisniowczyki, en Galitzia, Polonia. Se trasladó a Viena, donde estudió con Anton Bruckner y se dio a conocer como pianista, acompañando a cantantes de lieder y tocando música de cámara. Impartió clases particulares de piano y teoría de la música, estando Wilhelm Furtwängler, Anthony van Hoboken y Felix Salzer entre sus alumnos.

Las ideas de Schenker sobre el análisis fueron exploradas primero en su Tratado de armonía (Harmonielehre, 1906) y Contrapunto (Kontrapunkt, 2 vols., 1910 y 1922), y fueron desarrolladas en los dos periódicos que publicó, Der Tonwille (1921-24) y Das Meisterwerk in der Musik (1925-30), incluyendo ambos contenidos exclusivos de Schenker. El deseo de Schenker de que sus análisis fueran herramientas usadas por los intérpretes para un conocimiento más profundo de las obras que estuvieran interpretando se muestra en el hecho de que su edición de la últimas sonatas para piano de Ludwig van Beethoven incluyeran también análisis de las obras.

En 1932, Schenker publicó Cinco Análisis Musicales Gráficos (Fünf Urlinie-Tafeln), análisis de cinco obras utilizando la técnica analítica de mostrar capas de mayor y menor detalle musical, que ahora lleva su nombre. Tras la muerte de Schenker, se publicó su obra teórica incompleta Composición libre (Der freie Satz, 1935) (primero traducida al inglés por T. H. Kreuger en 1960 como una disertación en la Universidad de Iowa; una segunda y mejor traducción, por Ernst Oster, se publicó en 1979).

...Mientras sus teorías han sido puestas a prueba desde mitad de siglo por su rigidez y su ideología organicista, la amplia tradición analítica que inspiraron ha permanecido como principal en el estudio de la música tonal.” (Wikipedia, 26/vi/2010)

http://es.wikipedia.org/wiki/Heinrich_Schenker

 

Schenkerian analysis

Schenkerian analysis is a method of musical analysis of tonal music based on the theories of Heinrich Schenker. The goal of a Schenkerian analysis is to reveal the underlying structure of a tonal work; in fact its basic tenets can be viewed as a way of defining tonality in music. The primary means of describing the structure of a musical passage for the Schenkerian analyst is to show hierarchical relationships among the pitches of the passage. This can be done through making reductions of the music and through a specialized symbolic form of musical notation that Schenker devised to demonstrate various prolongational techniques.

The musical reductions of Schenkerian analysis are usually arrhythmic. This reflects Schenker's belief that the deep, long-range structure of a piece of music has no particular rhythm. This long-range structure is called the Fundamental Structure (Ursatz) in Schenkerian analysis, while the more surface aspects of the music are called the foreground or surface layer. So one could rephrase the previous statement as "the background of a musical composition is arhythmic," or, better yet, "rhythm is a characteristic of the musical foreground" (See Der Freie Satz section 21 and chapter 4). Open and closed noteheads, beams, and flags, which show rhythm in ordinary musical notation, are used in Schenkerian analysis to show hierarchical relationships between the pitch-events being analyzed.” (Wikipedia, 26/vi/2010)

http://en.wikipedia.org/wiki/Schenkerian_analysis

 

 

Fundamental structure

  (Redirected from Ursatz)

“In Schenkerian analysis, the fundamental structure (German: Ursatz) is a specific musical pattern that occurs at the most remote (or "background") level of structure. A basic elaboration of the tonic triad, it consists of the fundamental line accompanied by the bass arpeggiation. Hence the fundamental structure, like the fundamental line itself, takes one of three forms, according to which tonic triad pitch is the primary tone. The following is an example in C major, with the fundamental line descending from scale degree” (Wikipedia, 26/vi/2010)

http://en.wikipedia.org/wiki/Ursatz

 

 

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A Generative Theory of Tonal Music  /  Teoría generativa de la música tonal

 

LERDAHL, Fred y JACKENDOFF, Ray: A Generative Theory of Tonal Music

Preface

http://www.johnhalle.com/bard.classes/musilanguage/week3/lj.preface.pdf

RAR File

http://dc270.4shared.com/download/lSnrJ_9Z/A_Generative_Theory_of_Tonal_M.rar?tsid=20100917-150354-63141bd4

books.google

http://books.google.com.mx/books?id=6HGiEW33lucC&dq=LERDAHL,+Fred+y+JACKENDOFF,+Ray:+A+Generative+Theory+of+Tonal+Music&printsec=frontcover&source=bn&hl=es&ei=pLyTTIOpLJT4swPVnYTBCg&sa=X&oi=book_result&ct=result&resnum=4&ved=0CCwQ6AEwAw#v=onepage&q&f=true

AMAZON

http://www.amazon.ca/Generative-Theory-Tonal-Music/dp/026262107X

 

A Generative Theory of Tonal Music

Annotation (by Bill Tilghman):

http://www.music.indiana.edu/som/courses/rhythm/annotations/lerdahl83.html

 

Symposium

“Around Fred Lerdahl & Ray Jackendoff’s

Generative Theory of Tonal Music”

Ircam & ENS

11-12 January 2008

PROGRAM

http://recherche.ircam.fr/equipes/repmus/mamux/PrSympAng.pdf

 

 

Teoría generativa de la música tonal

Fred Lerdahl, Ray Jackendoff

Ediciones AKAL, 2003 - 407 páginas

“Convertida en un clásico desde su publicación en 1983, la presente obra construye un modelo de la comprensión musical desde el punto de vista de la ciencia cognitiva. El punto de partida es la búsqueda de una gramática de la música con la ayuda de la lingüística generativa. La teoría, ilustrada con numerosos ejemplos tomados de la música clásica occidental, pone en relación la superficie audible de una pieza con la estructura musical deducida inconscientemente por el oyente experimentado. Desde el punto de vista de la teoría de la música tradicional, ofrece muchas innovaciones, tanto por lo que respecta a la notación como al fondo de las teorías rítmica y de reducción.”

http://books.google.com.mx/books?id=91Ozkk-TRmoC&dq=isbn:8446015986

 

Teoría generativa de la música tonal

Fred Lerdahl / Ray Jackendoff

EDITORIAL Akal

Traductor Juan González-Castelao Martínez

N.° páginas 432

Año edición 2003

http://www.akal.com/libros/TeorIa-generativa-de-la-mUsica-tonal/9788446015987

 

Teoría generativa de la música tonal

Escrito por Fred Lerdahl, Ray Jackendoff

http://books.google.com.mx/books?id=91Ozkk-TRmoC&printsec=frontcover&source=gbs_ge_summary_r&cad=0#v=onepage&q&f=false

 

 

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TESIS DOCTORAL

ESTRUCTURA Y SIGNIFICADO EN LA MÚSICA SERIAL Y ALEATORIA

Alicia Díaz de la Fuente

Departamento de Filosofía y Filosofía Moral y Política

Facultad de Filosofía, Universidad Nacional de Educación a Distancia, 2005

Departamento de Filosofía y Filosofía Moral y Política, Facultad de Filosofía

Director de tesis: Dr. D. Simón Marchán Fiz

. Índice ……………………………………………………………...………….... 3

. Introducción ………………………………...……………………………….... 7

1. Singularidades del arte sonoro …………………………………..……….... 13

1.1. La música como lenguaje ……………………….………………..………....13

1.1.1. Sintáctica y semanticidad del sonido....………………….….…… 18

1.1.2 Formalismo versus contenidismo ……………………………….... 26

1.2. La música como actividad creadora y experiencia estética …………...……33

2. Fin de la tonalidad y quiebra de la representación. La música entre el azar

y la serie. ……………………...………………………………….……...……... 37

2. 1. Antecedentes de la música serial y aleatoria: la ruptura gramatical de

Schoenberg y Kandinsky …………………………………………………….... 37

2.1.1. Fin de la tonalidad y quiebra de la representación …………….... 37

2.1.1.1. El significado de la vanguardia ………………………... 38

2.1.1.2. Debussy y el dominio de lo simbólico ……………….... 44

2.1.1.3. Schoenberg, Kandinsky y la autonomía del sonido y el color.... 53

2.1.2. Tras la pista de una nueva gramática ……………………………. 76

2.1.2.1. Del Kandinsky analítico al Schoenberg dodecafónico…. 76

2.2. Radicalización de las vanguardias: ¿determinación o indeterminación? ..… 87

2.2.1. Una apuesta por la indeterminación ………………………………90

2.2.1.1. El azar en el arte: del happening de Cage al dripping de Pollock .... 90

2.2.1.2. Principios estético-musicales de John Cage ………… ...99

2.2.2. Una apuesta por la determinación ……..……………….……… 112

2.2.2.1. La matemática en el arte: de la geometrización de Klee a

las matrices boulezianas ………...………………………….… 112

2.2.2.2 Principios estético-musicales del serialismo de Pierre Boulez ……. 121

2.3. Consecuencias del serialismo y la aleatoriedad ………..………………… 131

2.3.1. De la matemática bouleziana a la fractalidad ……...…………… 134

2.3.2. Más allá de Cage: la conquista de la intemporalidad ...………… 137

3. El lenguaje musical como expresión de nuevos principios estéticos …….142

3.1. La apertura del signo musical …………….……………………………… 142

3.1.1. Naturaleza del signo musical …………...……………………… 143

3.1.2. Semanticidad del signo musical …..…………………………… 145

3.1.3. ¿Es la partitura gráfica un código notacional lingüístico? …..… 149

3.1.4. La apertura del signo musical, propiciadora de la dimensión

intersubjetiva del lenguaje …………………………..………………. 157

3.2. El giro lingüístico en las vanguardias musicales de los años cincuenta del

siglo XX. ……………………………………………………………………… 162

3.2.1. Quiebra sintáctica y semántica de la música aleatoria …...…….. 162

3.2.2. Proliferación de signos y mutabilidad sincrónica …..………….. 164

3.2.3. Lenguaje serial y lenguaje aleatorio: homogeneidad psicoperceptiva,

heterogeneidad gramatical ..………..………………………………… 171

4. Los modos de ser de la obra artística …………………………………….180

4.1.Génesis del acto creador: el azar y la matemática como principios generadores

de arte ………………………………………………………………………… 180

4.1.1. El nuevo juego de la reflexión poética ………..……………….. 182

4.1.2. Obras autográficas versus obras alográficas: denotación y ejecución .. 187

4.1.3. Estatuto ontológico de la música serial y aleatoria ……..……… 191

4.2. Las distintas manifestaciones del serialismo y la aleatoriedad .……….… 199

5. Una lectura deconstructiva de Cage y Boulez ..…………………………. 204

5.1. Análisis estético-musical del Concierto para piano preparado y orquesta de

cámara de John Cage ……………...………………………………………….. 204

5.1.1. Una nueva estética a través del azar ……………………………. 208

5.1.2. Concierto para piano preparado y orquesta de cámara ……..….. 215

5.1.2.1. Análisis deconstructivo ……...……………………….. 216

5.1.2.2. Ejecución y escucha ………………………………….. 227

5.2. Análisis estético-musical de las Estructuras para dos pianos Ia de Pierre

Boulez…………………………………………………………………………. 231

5.2.1. Una nueva estética a través de la hiper-formalización ..……….. 236

5.2.2. Estructuras para dos pianos ……..……………………………... 240

5.2.2.1. Análisis deconstructivo ………………………………..241

5.2.2.2. Ejecución y escucha ……………………………..……256

6. Los modos de ser de la experiencia estética ….…………….…………… 266

6.1. La experiencia estética como proceso …………………………………… 266

6.1.1. Aplazamiento y deconstrucción ………….…………………….. 271

6.1.2. La interpretación entre el azar y la serie …………..…………… 282

6.2. Serialismo y aleatoriedad: un posible estrato común ..…………………… 288

6.2.1. Cuando serie y azar se dan la mano …………………...……….. 298

.Conclusión …………………………………………………………………… 312

.Anexo ……... ………………………………………………………………… 319

.Bibliografía ……………………………………………..…………………… 378

http://www.uned.es/dpto_fim/publicaciones/alicia_1.pdf

 

 

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Ambient music

 

Ambient music

Ambient music is a musical genre that focuses largely on the timbral characteristics of sounds, often organized or performed to evoke an "atmospheric". "visual” or "unobtrusive" quality.

…The roots of ambient music go back to the early 20th century. In particular, the period just before and after the first world war gave rise to two significant Art Movements that encouraged experimentation with various musical (and non musical) forms, while rejecting more conventional, tradition-bound styles of expression. These art movements were called Futurism and Dadaism. Aside from being known for their painters and writers, these movements also attracted experimental and 'anti-music' musicians such as Francesco Balilla Pratella of the pre-war Futurism movement and Kurt Schwitters and Erwin Schulhoff of the post-war Dadaist movement. The latter movement played an influential role in the musical development of Erik Satie.” (Wikipedia, 26/vi/2010)

http://en.wikipedia.org/wiki/Ambient_music

 

Ambient

“El ambient es un género musical en el cual el sonido es más importante que las notas. Generalmente se identifica por ser profundamente atmosférica y ambiental. La música ambient evolucionó desde las formas musicales semi-audibles de principios del Siglo XX, del impresionismo de Erik Satie, a través de la música concreta y el minimalismo de Terry Riley y Philip Glass, y el deliberado acercamiento subaudible de Brian Eno, hasta su uso en la música electrónica.

Acontecimientos posteriores encontraron elementos "soñadores" no-lineales de la música ambient aplicados a algunas formas de música rítmica presentes en las salas de chill-out en los raves y otros eventos de baile, pero siempre con la característica primaria que la música intenta atravesar la conciencia del oyente mientras crea su efecto sobre éste.” (Wikipedia, 26/vi/2010)

http://es.wikipedia.org/wiki/Ambient

 

 

Brian Eno

Brian Peter George St John le Baptiste de la Salle Eno (born 15 May 1948), commonly known as Brian Eno and previously as simply Eno (pronounced /ˈiːnoʊ/), is an English musician, composer, record producer, music theorist, singer and visual artist, best known as one of the principal innovators of ambient music.” (Wikipedia, 26/vi/2010)

http://en.wikipedia.org/wiki/Brian_Eno

 

Brian Eno

Brian Peter George St. John le Baptiste de la Salle Eno, Brian Eno o, simplemente, Eno (Woodbridge, Suffolk, Reino Unido, 15 de mayo de 1948) es un compositor de música electrónica que empezó tocando con Roxy Music. Tras abandonar el grupo comenzó una carrera en solitario que partió del art rock para llegar a la música ambient y a todo tipo de experimentos de vanguardia. El propio término «música ambient» se acuñó a partir de su serie de álbumes inspirados en el muzak, entre ellos Music for Airports, The Plateaux of Mirror, Day of Radiance y On Land.” (Wikipedia, 26/vi/2010)

http://es.wikipedia.org/wiki/Brian_Eno

 

El británico Brian Eno trae su “arte generativo” a México

77 millones de pinturas se compone de 360 cuadros permutadas de cuatro en cuatro

El creador vanguardista impartirá una conferencia magistral en el Teatro de la Ciudad

Juan José Olivares, Periódico La Jornada, Jueves 25 de marzo de 2010, p. 3

“trae a México su reciente “paisaje sonoro”: 77 millones de pinturas, pieza de arte generativo audiovisual que se sirve de un software (hay que recordar que es el creador del archivo de sonido de inicio de sesión de Windows 95, que aún se encuentra en las versiones actuales) desarrollado específicamente para mezclar elementos visuales –como cuadros, pinturas, grabados en diapositivas– y sonoros realizados por él mismo a lo largo de 20 años.”

http://www.jornada.unam.mx/2010/03/25/index.php?section=cultura&article=a03n1cul

 

Brian Eno 77 Million Paintings Interview

http://www.youtube.com/watch?v=VRkNrWp6tLg

 

 

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Evolución y Educación

 

Chaos seems to aid learning
By Kimberly Patch, Technology Research News, May 5/12, 2004

“Researchers from Core Research for Evolutional Science and Technology (CREST) in Japan have built a computer simulation of the inferior olive, a portion of the brain that probably relays errors in movement to the cerebellum. It has been difficult to explain the mechanics of this relationship because inferior olive cells that connect to the cerebellum fire slowly, and this does not fit well with the common hypothesis that high-fidelity error signals are needed for efficient learning.”

http://www.trnmag.com/Stories/2004/050504/Chaos_seems_to_aid_learning_050504.html

 

CCK08: Chaos is good!

Posted by Sarah Stewart, Saturday, September 27, 2008

“Chaos appears to be inevitable in courses where a connectivist approach is taken to learning. You only have to look at the 'Connectivism and Connective Knowledge' online course that is currently running, and to a lessor degree 'Facilitating Online Communities'.”

http://sarah-stewart.blogspot.com/2008/09/cck08-chaos-is-good.html

 

International Society for Presence Research (ISPR)

“The International Society for Presence Research (ISPR) supports academic research related to the concept of (tele)presence, commonly referred to as a sense of 'being there' in a virtual environment and more broadly defined as an illusion of nonmediation in which users of any technology overlook or misconstrue the technology's role in their experience.”

http://www.temple.edu/ispr/

 

International Society for Presence Research (ISPR)

Examples of Presence

http://www.temple.edu/ispr/frame_examples.htm

 

 

Evolution as Fact, Theory, and Path

T. Ryan Gregory

http://www.springerlink.com/content/21p11486w0582205/fulltext.pdf

 

Evolution: Education and Outreach

revista con artículos disponibles libremente

http://www.springerlink.com/content/120878/

 

 

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Researchers teach 'Second Life' avatar to think

By Michael Hill, Associated Press, May 18, 2008

“Edd Hifeng barely merits a second glance in "Second Life." A steel-gray robot with lanky limbs and linebacker shoulders, he looks like a typical avatar in the popular virtual world.

But Edd is different.

His actions are animated not by a person at a keyboard but by a computer. Edd is a creation of artificial intelligence, or AI, by researchers at Rensselaer Polytechnic Institute, who endowed him with a limited ability to converse and reason. It turns out "Second Life" is more than a place where pixelated avatars chat, interact and fly about. It's also a frontier in AI research because it's a controllable environment where testing intelligent creations is easier.”

http://ap.google.com/article/ALeqM5jZy-cAS6fmqoTCIH9TXL8JHu6frAD90O7EDG0

 

 

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Smart Computer Learns From Video

PhysOrg.com, June 23, 2010

Provided by ETH Zurich

“Swiss researchers have written a computer programme that is able to analyse temporal and spatial patterns of moving objects, and on top of that is capable of learning. This would be a significant aid in traffic monitoring.”

http://www.physorg.com/news196521871.html

 

 

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Immortal avatars: Back up your brain, never die

Linda Geddes, New Scientist, 07 June 2010

 “…Ultimately, however, they aim to create a personalised, conscious avatar embodied in a robot - effectively enabling you, or some semblance of you, to achieve immortality. "If you can upload yourself into this digital form, it could live forever," says Nick Mayer of Lifenaut, a US company that is exploring ways to build lifelike avatars. "It really is a way of avoiding death."

http://www.newscientist.com/article/mg20627631.100-immortal-avatars-back-up-your-brain-never-die.html

 

 

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