Emergence of group behavior in multiagent systems using self trained agent communication

Author

Mackin, Kenneth J. ; Tazaki, Eiichiro

Author_Institution

Dept. of Control & Syst. Eng., Toin Univ. of Yokohama, Japan

Volume

4

fYear

1999

fDate

6/21/1905 12:00:00 AM

Firstpage

2241

Abstract

Multiagent systems, in which independent software agents interact with each other to achieve common goals, complete concurrent distributed tasks under autonomous control. We propose a method applying genetic programming (GP) to allow agents to autonomously learn effective agent communication messaging in order to achieve group behavior. A software simulation of a multiagent system will be used to observe the effectiveness of the proposed method. Using the proposed method, emergence of a compact and efficient agent communication protocol for the multiagent system was observed

Keywords

genetic algorithms; multi-agent systems; self-organising feature maps; GP; agent communication protocol; autonomous control; concurrent distributed tasks; effective agent communication messaging; genetic programming; group behavior emergence; multiagent system; multiagent systems; self trained agent communication; software simulation; Communication system control; Computational modeling; Concurrent computing; Control systems; Distributed computing; Genetic programming; Multiagent systems; Protocols; Software agents; Systems engineering and theory;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks, 1999. IJCNN '99. International Joint Conference on

ISSN

1098-7576

Print_ISBN

0-7803-5529-6

Type

conf

DOI

10.1109/IJCNN.1999.833410

Filename

833410