Exploration and Exploitation Trade-Off in Multiagent Learning

Authors:
Keiki Takadama;Katsunori Shimohara
Affiliations:
-;-
Venue:
ICCIMA '01 Proceedings of the Fourth International Conference on Computational Intelligence and Multimedia Applications
Year:
2001

Citing 0
Cited 2

Toward Cumulative Progress in Agent-Based Simulation

Proceedings of the Joint JSAI 2001 Workshop on New Frontiers in Artificial Intelligence
Interpretation by Implementation for Understanding a Multiagent Organization

Computational & Mathematical Organization Theory

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper focuses on the trade-off between exploration and exploitation in multiagentlearning and explores some fundamental factors that contribute to clarifying this trade-offThrough inventive simulations on distributed constraint satisfaction problems in multiagentenvironments, the following implications are revealed: (1) the trade-off between explorationand exploitation at the collective level is not easy to be solved when considering the trade-offat the individual level; but (2) the trade-off at the collective level can be solved by introducinga simple gradient search in the trade-off at the individual level.