Evolution of Self-Organized Task Specialization in Robot Swarms

Created by W.Langdon from gp-bibliography.bib Revision:1.3963

@Article{oai:HAL:hal-01378166v1,
  author =       "Eliseo Ferrante and Ali Turgut and 
                 Edgar Duenez-Guzman and Marco Dorigo and Tom Wenseleers",
  title =        "Evolution of Self-Organized Task Specialization in
                 Robot Swarms",
  journal =      "PLoS Computational Biology",
  year =         "2015",
  volume =       "11",
  pages =        "1004273--1004273",
  month =        aug # " 6",
  keywords =     "genetic algorithms, genetic programming, artificial
                 intelligence, machine learning, multiagent systems
                 nonlinear sciences, adaptation and self-organising
                 systems",
  ISSN =         "1553-734X; 1553-7358",
  bibsource =    "OAI-PMH server at api.archives-ouvertes.fr",
  identifier =   "hal-01378166",
  DOI =          "doi:10.1371/journal.pcbi.1004273.s009",
  language =     "en",
  oai =          "oai:HAL:hal-01378166v1",
  relation =     "info:eu-repo/semantics/altIdentifier/doi/10.1371/journal.pcbi.1004273.s009",
  URL =          "https://hal.archives-ouvertes.fr/hal-01378166",
  URL =          "https://hal.archives-ouvertes.fr/hal-01378166/document",
  URL =          "https://hal.archives-ouvertes.fr/hal-01378166/file/2015_PlosComputationalBiology.pdf",
  DOI =          "doi:10.1371/journal.pcbi.1004273",
  size =         "21 pages",
  abstract =     "Division of labour is ubiquitous in biological
                 systems, as evidenced by various forms of complex task
                 specialization observed in both animal societies and
                 multicellular organisms. Although clearly adaptive, the
                 way in which division of labor first evolved remains
                 enigmatic, as it requires the simultaneous
                 co-occurrence of several complex traits to achieve the
                 required degree of coordination. Recently, evolutionary
                 swarm robotics has emerged as an excellent test bed to
                 study the evolution of coordinated group-level
                 behaviour. Here we use this framework for the first
                 time to study the evolutionary origin of behavioural
                 task specialization among groups of identical robots.
                 The scenario we study involves an advanced form of
                 division of labour, common in insect societies and
                 known as task partitioning, whereby two sets of tasks
                 have to be carried out in sequence by different
                 individuals. Our results show that task partitioning is
                 favoured whenever the environment has features that,
                 when exploited, reduce switching costs and increase the
                 net efficiency of the group, and that an optimal mix of
                 task specialists is achieved most readily when the
                 behavioural repertoires aimed at carrying out the
                 different subtasks are available as pre-adapted
                 building blocks. Nevertheless, we also show for the
                 first time that self-organized task specialization
                 could be evolved entirely from scratch, starting only
                 from basic, low-level behavioural primitives, using a
                 nature-inspired evolutionary method known as
                 Grammatical Evolution. Remarkably, division of labour
                 was achieved merely by selecting on overall group
                 performance, and without providing any prior
                 information on how the global object retrieval task was
                 best divided into smaller subtasks. We discuss the
                 potential of our method for engineering adaptively
                 behaving robot swarms and interpret our results in
                 relation to the likely path that nature took to evolve
                 complex sociality and task specialization.",
  notes =        "Is this GP?",
}

Genetic Programming entries for Eliseo Ferrante Ali Turgut Edgar Duenez-Guzman Marco Dorigo Tom Wenseleers

Citations