A study of evolutionary multiagent models based on symbiosis

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@Article{DBLP:journals/tsmc/EguchiHHO06,

• author = "Toru Eguchi and Kotaro Hirasawa and Jinglu Hu and Nathan Ota",
• title = "A study of evolutionary multiagent models based on symbiosis",
• journal = "IEEE Transactions on Systems, Man, and Cybernetics, Part B",
• volume = "36",
• number = "1",
• year = "2006",
• pages = "179--193",
• month = feb,
• keywords = "genetic algorithms, genetic programming, decision making, evolutionary computation, graph theory, learning (artificial intelligence), multi-agent systems, directed graph, evolutionary multiagent models, genetic network programming, match type tile-world, nash equilibria, symbiosis multiagent systems, symbiotic evolution, symbiotic learning, virtual model, Evolutionary computation, multiagent systems, symbiosis, tile-world",
• bibsource = "DBLP, http://dblp.uni-trier.de",
• DOI = "doi:10.1109/TSMCB.2005.856720",
• size = "15 pages",
• abstract = "Multiagent Systems with Symbiotic Learning and Evolution (Masbiole) has been proposed and studied, which is a new methodology of Multiagent Systems (MAS) based on symbiosis in the ecosystem. Masbiole employs a method of symbiotic learning and evolution where agents can learn or evolve according to their symbiotic relations toward others, i.e., considering the benefits/losses of both itself and an opponent. As a result, Masbiole can escape from Nash Equilibria and obtain better performances than conventional MAS where agents consider only their own benefits. This paper focuses on the evolutionary model of Masbiole, and its characteristics are examined especially with an emphasis on the behaviours of agents obtained by symbiotic evolution. In the simulations, two ideas suitable for the effective analysis of such behaviors are introduced; {"}Match Type Tile-world (MTT){"} and {"}Genetic Network Programming (GNP){"}. MTT is a virtual model where tile-world is improved so that agents can behave considering their symbiotic relations. GNP is a newly developed evolutionary computation which has the directed graph type gene structure and enables to analyse the decision making mechanism of agents easily. Simulation results show that Masbiole can obtain various kinds of behaviours and better performances than conventional MAS in MTT by evolution.",

}

Genetic Programming entries for Toru Eguchi Kotaro Hirasawa Jinglu Hu Nathan Ota

Citations