Title :
Agent swarm regression network ASRN
Author :
Chow, Chi-Kin ; Tsui, Hung-Tat
Author_Institution :
Dept. of Electron. Eng., Chinese Univ. of Hong Kong, China
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;
Conference_Titel :
Systems, Man and Cybernetics, 2004 IEEE International Conference on
Print_ISBN :
0-7803-8566-7
DOI :
10.1109/ICSMC.2004.1401087
