Genetic network programming with automatically defined groups for assigning proper roles to multiple agents
Author(s) -
Tadahiko Murata,
Takashi Nakamura
Publication year - 2005
Publication title -
citeseer x (the pennsylvania state university)
Language(s) - English
Resource type - Conference proceedings
ISBN - 1-59593-010-8
DOI - 10.1145/1068009.1068294
Subject(s) - genetic programming , computer science , architecture , task (project management) , genetic algorithm , artificial intelligence , tree (set theory) , mathematical optimization , machine learning , mathematics , engineering , art , mathematical analysis , systems engineering , visual arts
In this paper, we apply a Genetic Network Programming (GNP) Architecture using Automatically Defined Groups (ADG) to a multi-agent problem where cooperation of agents are required. GNP is a kind of evolutionary methods inspired from Genetic Programming (GP). While GP has a tree architecture, GNP has a network architecture with which an agent works in the virtual world. In GNP with ADG, each agent is assigned to a group according to its role to complete some task of a cooperative problem. We consider two types of problems in this paper: one problem is to assign an appropriate role to each agent according to its ability, and the other is to assign a proper role to each agent with the same ability. While the first problem has the specific conditions as for the ability of an agent, the latter is a general problem. We show the effectiveness of GNP with ADG through computer simulations on the two types of load transportation problems.
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