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..
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Evolution and Evolutionary Systems LINKS to Applications Evolución y Sistemas Evolutivos LIGAS
a Aplicaciones www.fgalindosoria.com/eac/evolucion/
www.fgalindosoria.com/eac/
Fernando Galindo Soria
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Evolución y Sistemas Evolutivos, Sistemas Afectivos y
Sistemas Concientes
Evolución y Sistemas Evolutivos Sistemas Afectivos Sistemas Concientes
Matrices
Evolutivas y Dinámica Dimensional
Creación
de la página www Cd. De México a 2 de Junio del 2001
Ultimas actualizaciones 27 de Mayo del 2007, 9 de Diciembre del
2008, 9 de Julio del 2009, 11 de Julio del 2010
Applications /
Aplicaciones
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*********************************************************** Robótica
evolutiva
Con la robótica
evolutiva pretenden desarrollar máquinas que evolucionen “Esperamos que un robot pre-sabio evolucione
a sabio por aprendizaje de su mundo mediante la experimentación en él y por
interacción con personas mediante el lenguaje simbólico y el lenguaje
corporal.” Doctor José
Negrete Martínez Pionero de
la inteligencia artificial en México. E X P R E S O Jueves 24 de Mayo de 2007 http://www.expreso.com.mx/edicionimpresa/20070524/1/16.pdf Evolution
trains robot teams “Evolution has
worked pretty well for biological systems, so why not apply it to the systems
that control robots? By Kimberly
Patch, Technology Research News, May 19/26, 2004 http://www.trnmag.com/Stories/2004/051904/Evolution_trains_robot_teams_051904.html York
investigates evolving ‘swarm’ robots Media Information: David Garner 01904 432153 Communications Office - University of York, 13 March 2008 http://www.york.ac.uk/admin/presspr/pressreleases/symbrion.htm ALIFE Conference to Reveal New Approaches to Robot Role-Play The use of artificial
evolution to enable robots to assume roles will be described by researchers
at the ALIFE conference in Winchester http://www.ecs.soton.ac.uk/about/news/1963 *********************************************************** Evolving
Inventions Evolving
Inventions By John R. Koza, Martin A. Keane and Matthew J.
Streeter February 2003 Scientific American Magazine “Computer
programs that function via Darwinian evolution are creating inventions that
are novel and useful enough to be patented” http://www.sciam.com/article.cfm?id=evolving-inventions Invención por evolución Koza, John R.; Keane, Martin A. y Streeter, Matthew J. http://www.investigacionyciencia.es/03028113000473/Invenci%C3%B3n_por_evoluci%C3%B3n.htm ************************************************** Network Inference
Comparing
Evolutionary Algorithms on the Problem of Network Inference Christian
Spieth, Rene Worzischek, Felix Streichert Centre for Bioinformatics, T¨ubingen (ZBIT), T¨ubingen, German http://www.ra.cs.uni-tuebingen.de/publikationen/2006/spieth06eas.pdf ACM Comparing mathematical models on the problem of network
inference Proceedings of the 8th annual conference on Genetic and
evolutionary computation Christian Spieth, Nadine Hassis, Felix Streichert “In this
paper we address the problem of finding gene regulatory networks from
experimental DNA microarray data. We focus on the evaluation of the
performance of different mathematical models on the inference problem. They
are used to model the underlying dynamic system of artificial regulatory
networks. The dynamics of the artificial systems represent different basic
types of behavior,dimensionality and mathematical properties. They are all
created with three commonly used approaches, namely linear weight matrices,
H-systems, and S-systems. Due to the complexity of the inference problem,
some researchers suggested evolutionary algorithms for this purpose. However,
in many publications only one algorithm is used without any comparison to
other optimization methods. Thus, we introduce a framework to systematically
apply evolutionary algorithms for further comparative analysis.” http://portal.acm.org/tipsvc.cfm?id=1144045&sess=%27%2A%5CS%2CRL%5B%2B3%20%20%20%0A ************************************************** Automatic paper
generator http://pdos.csail.mit.edu/scigen/ Welcome to NeOn! Thursday, 25 May 2006 “NeOn is a 14.7 million Euros project involving 14 European partners and
co-funded by the European Commission’s Sixth Framework Programme under grant
number IST-2005-027595. NeOn started in March 2006 and has a duration of 4
years. Our aim is to advance the state of the art in using ontologies for large-scale
semantic applications in the distributed organizations. Particularly, we aim
at improving the capability to handle multiple networked ontologies
that exist in a particular context, are created collaboratively,
and might be highly dynamic and constantly evolving.” http://www.neon-project.org/web-content/ Managing fisheries with semantic technologies ICT Results, June 25, 2008 “The NeOn team is creating an
industrial-strength development toolkit for semantic applications, software
that works with the meaning of data rather than simply its label or file
name.” http://cordis.europa.eu/ictresults/index.cfm/section/news/tpl/article/BrowsingType/Features/ID/89817 |