Bacterially inspired evolving system with an application to time series prediction

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@Article{Rolania:2013:ASC,

• author = "D. Barrios Rolania and J. M. Font and D. Manrique",
• title = "Bacterially inspired evolving system with an application to time series prediction",
• journal = "Applied Soft Computing",
• volume = "13",
• number = "2",
• pages = "1136--1146",
• year = "2013",
• keywords = "genetic algorithms, genetic programming, Natural computing, Bio-inspired computation, Synthetic biology",
• ISSN = "1568-4946",
• DOI = "doi:10.1016/j.asoc.2012.10.012",
• URL = "http://www.sciencedirect.com/science/article/pii/S1568494612004632",
• abstract = "This paper explores the synergies between evolutionary computation and synthetic biology, developing an in silico evolutionary system that is inspired by the behaviour 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 decentralised, 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 analysing 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.",

}

Genetic Programming entries for Dolores Barrios Rolania Jose M Font Daniel Manrique Gamo

Citations