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Teoría y Práctica de los
SISTEMAS EVOLUTIVOS, Segunda Edición, January 1, 2010
En este trabajo se presentan una serie de ideas generadas
durante más de veinte años y en las que en esencia se plantea 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. Lo anterior se podría aplicar para
entender y aprovechar el comportamiento de las diferentes manifestaciones
de los procesos evolutivos, mediante el desarrollo y uso de herramientas de
una "Ingeniería Evolutiva". Un sistema evolutivo tiende a mejorar
su interrelación con el medio y en general es "hermoso" y natural
dentro de su contexto
http://www.lulu.com/spotlight/smartdsign
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Cosmic Evolution: The Rise of Complexity in
Nature
 Eric 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
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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
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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)
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
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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
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”
www.elsevier.com/wps/find/bookdescription.cws_home/677950/description#description
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Evolutionary
Computer Music
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
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Evolution and
the Theory of Games
John Maynard Smith
University of
Sussex
Cambridge University Press, 1982
“Professor John Maynard Smith has written an account
of a new way of thinking about evolution which has been developed in the
last ten years. The theory of games, first developed to analyse
economic behaviour, is modified so that it can be
applied to evolving populations. John Maynard Smith's concept of an
evolutionarily stable strategy is relevant whenever the best thing for an
animal or plant to do depends on what others are doing. The theory leads to
testable predictions about the evolution of behaviour,
of sex and genetic systems, and of growth and life history patterns. This
book contains the first full account of the theory, and of the data
relevant to it. The account is aimed at senior undergraduate and graduate
students, teachers and research workers in animal behaviour,
population genetics and evolutionary biology. The book will also be of
interest to mathematicians and game theorists; the mathematics has been
largely confined to appendixes so that the main text may be easily followed
by biologists.” (FGS Link, 26/vii/2010)
http://www.cambridge.org/catalogue/catalogue.asp?isbn=0521288843
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