DocumentCode
3207695
Title
Cooperative agents through bidding
Author
Qi, Dehu ; Sun, Ron
Author_Institution
Comput. Sci. Dept., Lamar Univ., Beaumont, TX, USA
fYear
2004
fDate
8-10 Nov. 2004
Firstpage
444
Lastpage
449
Abstract
One of the main research topics in multiagent systems is learning cooperation among agents. This paper presents a multiagent reinforcement learning approach with bidding. Self-interested agents cooperate with each other through bidding and evolutionary computation. We tested the approach to the TSP problem. The experimental results show our approach can achieve a certain level of performance in problem solving.
Keywords
evolutionary computation; learning (artificial intelligence); multi-agent systems; problem solving; travelling salesman problems; cooperative agent; evolutionary computation; multiagent system; problem solving; reinforcement learning; Cognitive science; Communication system control; Computer science; Evolutionary computation; Genetic algorithms; Learning; Multiagent systems; Problem-solving; Sun; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Reuse and Integration, 2004. IRI 2004. Proceedings of the 2004 IEEE International Conference on
Print_ISBN
0-7803-8819-4
Type
conf
DOI
10.1109/IRI.2004.1431501
Filename
1431501
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