Agent swarm regression network ASRN

Author

Chow, Chi-Kin ; Tsui, Hung-Tat

Author_Institution

Dept. of Electron. Eng., Chinese Univ. of Hong Kong, China

Volume

6

fYear

2004

fDate

10-13 Oct. 2004

Firstpage

5609

Abstract

A multi-agent system (MAS), with independent software agents interacting with each other to achieve common goals will complete concurrent distributed tasks under autonomous control. In this paper, novel RBF regression network \´\´agent swarm regression network ASRN" is proposed and trained by a MAS. Each neuron of the ASRN is considered as an agent, which consists of per-defined simple agent behavior set. After a sufficient number of iterations, the weights of neurons can be determined. Two sets of experiment are examined to observe the effectiveness of the proposed method.

Keywords

learning (artificial intelligence); multi-agent systems; radial basis function networks; software agents; RBF regression network; agent swarm regression network; autonomous control; concurrent distributed tasks; independent software agents; multi-agent system; per-defined simple agent behavior set; Communication system control; Control systems; Interpolation; Laboratories; Low earth orbit satellites; Multiagent systems; Neurons; Radial basis function networks; Signal processing; Support vector machines;

fLanguage

English

Publisher

ieee

Conference_Titel

Systems, Man and Cybernetics, 2004 IEEE International Conference on

ISSN

1062-922X

Print_ISBN

0-7803-8566-7

Type

conf

DOI

10.1109/ICSMC.2004.1401087

Filename

1401087