Observatorio de I+D+i UPM

Memorias de investigación
Artículos en revistas:
Bacterially Inspired Evolving System with an Application to Time Series Prediction (Aceptado)
Año:2011
Áreas de investigación
  • Ciencias de la computación y tecnología informática
Datos
Descripción
This paper explores the synergies between evolutionary computation and synthetic biology, developing an in silico evolutionary system that is inspired by the behavior of bacterial populations living in continuously changing environments. This system creates a 3D environment seeded with a simulated population of bacteria that eat, reproduce, interact with each other and with the environment and eventually die. This provides a 3D framework implementing an evolutionary process. The subject of the evolution is each bacterium's internal process, defining its interactions with the environment. The evolutionary goal is the survival of the population under successive, continuously changing environmental conditions. The key advantage of this bacterial evolutionary system is its decentralized, asynchronous, parallel and self-adapting general-purpose evolutionary process.We describe this system and present the results of an application to the evolution of a bacterial population that learns how to predict the presence or absence of food in the environment by analyzing three input signals from the environment. The resulting populations successfully evolve by continuously improving their fitness under different environmental conditions, demonstrating their adaptability to a fluctuating medium.
Internacional
Si
JCR del ISI
Si
Título de la revista
Applied soft computing
ISSN
1568-4946
Factor de impacto JCR
2,612
Información de impacto
La revista sí es JCR del ISI. El formulario web da un error al modificar dicho campo y no permite marcar la opción "Sí".
Volumen
DOI
http://dx.doi.org/10.1016/j.asoc.2012.10.012
Número de revista
Desde la página
1
Hasta la página
19
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: Departamento: Inteligencia Artificial
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