Literature DB >> 11580880

Evolving collective behavior in an artificial ecology.

C R Ward1, F Gobet, G Kendall.   

Abstract

Collective behavior refers to coordinated group motion, common to many animals. The dynamics of a group can be seen as a distributed model, each "animal" applying the same rule set. This study investigates the use of evolved sensory controllers to produce schooling behavior. A set of artificial creatures "live" in an artificial world with hazards and food. Each creature has a simple artificial neural network brain that controls movement in different situations. A chromosome encodes the network structure and weights, which may be combined using artificial evolution with another chromosome, if a creature should choose to mate. Prey and predators coevolve without an explicit fitness function for schooling to produce sophisticated, nondeterministic, behavior. The work highlights the role of species' physiology in understanding behavior and the role of the environment in encouraging the development of sensory systems.

Mesh:

Year:  2001        PMID: 11580880     DOI: 10.1162/106454601753139005

Source DB:  PubMed          Journal:  Artif Life        ISSN: 1064-5462            Impact factor:   0.667


  6 in total

1.  Speciation with gene flow in a heterogeneous virtual world: can physical obstacles accelerate speciation?

Authors:  Abbas Golestani; Robin Gras; Melania Cristescu
Journal:  Proc Biol Sci       Date:  2012-04-18       Impact factor: 5.349

2.  Predator confusion is sufficient to evolve swarming behaviour.

Authors:  Randal S Olson; Arend Hintze; Fred C Dyer; David B Knoester; Christoph Adami
Journal:  J R Soc Interface       Date:  2013-06-05       Impact factor: 4.118

3.  Selection methods regulate evolution of cooperation in digital evolution.

Authors:  Pawel Lichocki; Dario Floreano; Laurent Keller
Journal:  J R Soc Interface       Date:  2013-10-23       Impact factor: 4.118

4.  Evolution of Collective Behaviour in an Artificial World Using Linguistic Fuzzy Rule-Based Systems.

Authors:  Jure Demšar; Iztok Lebar Bajec
Journal:  PLoS One       Date:  2017-01-03       Impact factor: 3.240

5.  Emergence of Swarming Behavior: Foraging Agents Evolve Collective Motion Based on Signaling.

Authors:  Olaf Witkowski; Takashi Ikegami
Journal:  PLoS One       Date:  2016-04-27       Impact factor: 3.240

6.  Evolving flocking in embodied agents based on local and global application of Reynolds' rules.

Authors:  Rita Parada Ramos; Sancho Moura Oliveira; Susana Margarida Vieira; Anders Lyhne Christensen
Journal:  PLoS One       Date:  2019-10-29       Impact factor: 3.240

  6 in total

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