Evolution of Self-Organized Task Specialization in Robot Swarms

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@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