TY - JOUR
T1 - Multi Agent Systems with Symbiotic Learning and Evolution -Masbiole- and Its Application
AU - Hirasawa, Kotaro
AU - Nakanishi, Katsushige
AU - Eguchi, Toru
AU - Hu, Jinglu
PY - 2003/1
Y1 - 2003/1
N2 - Recently, systems are becoming more complex and larger than ever, so numerous attempts have been made to introduce biological features into artificial systems, because many biological systems in the nature exist as one of the most complex systems. Multi agent system with symbiotic learning and evolution have been recently proposed. It is named Masbiole. In this paper, Masbiole is reviewed and the method for evolving multi agent systems is proposed. From simulations on a multi objective knapsack problem, it has been clarified that Masbiole has better performance than that of conventional multi objective genetic algorithms.
AB - Recently, systems are becoming more complex and larger than ever, so numerous attempts have been made to introduce biological features into artificial systems, because many biological systems in the nature exist as one of the most complex systems. Multi agent system with symbiotic learning and evolution have been recently proposed. It is named Masbiole. In this paper, Masbiole is reviewed and the method for evolving multi agent systems is proposed. From simulations on a multi objective knapsack problem, it has been clarified that Masbiole has better performance than that of conventional multi objective genetic algorithms.
KW - evolution
KW - learning
KW - multi agent system
KW - pareto optimal solutions
KW - symbiosis
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U2 - 10.1541/ieejeiss.123.67
DO - 10.1541/ieejeiss.123.67
M3 - Article
AN - SCOPUS:27944457005
SN - 0385-4221
VL - 123
SP - 67
EP - 74
JO - IEEJ Transactions on Electronics, Information and Systems
JF - IEEJ Transactions on Electronics, Information and Systems
IS - 1
ER -