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Memorias de investigación
Artículos en revistas:
Bacterially Inspired Evolution of Intelligent Systems under Constantly Changing Environments (Enviado)
Año:2012
Áreas de investigación
  • Ciencias de la computación y tecnología informática
Datos
Descripción
This paper explores the capabilities of open-ended bio-inspired evolutionary construction of intelligent systems under changing environments. We present and analyze extensive results of the bacterial evolutionary system. This system creates 3D environments that simulate real constantly changing environments. Populations of artificial bacteria constantly evolve their inner biological processes in these environments as they perform every action programmed in their life cycle. This results in a decentralized, asynchronous, parallel and self-adapting general-purpose evolutionary process whose only goal is the survival of the bacterial population under successive, continuously changing environmental conditions. Results show the problem independence and general-purpose capabilities of the system by making it evolve fuzzy rule-based systems under different environments. Robustness and fault tolerance capabilities are also tested by facing the bacterial evolutionary system to sudden changes in the environment. Evolution is open-ended as there is no need to restart the system when changes take place. Artificial bacteria self-adapt themselves in real time in order to guarantee their survival.
Internacional
Si
JCR del ISI
Si
Título de la revista
Soft Computing
ISSN
1432-7643
Factor de impacto JCR
1,88
Información de impacto
Datos JCR del año 2011
Volumen
DOI
Número de revista
Desde la página
0
Hasta la página
24
Mes
SIN MES
Ranking
Esta actividad pertenece a memorias de investigación
Participantes
  • Autor: José María Font Fernández (UPM)
  • Autor: Daniel Manrique Gamo (UPM)
  • Autor: Maria Dolores Barrios Rolania (UPM)
Grupos de investigación, Departamentos, Centros e Institutos de I+D+i relacionados
  • Creador: Grupo de Investigación: Grupo de Inteligencia Artificial (LIA)
  • Grupo de Investigación: Teoría de Aproximación Constructiva y Aplicaciones
  • Departamento: Inteligencia Artificial
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