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ML
1998
ACM

Conjectural Equilibrium in Multiagent Learning

13 years 3 months ago
Conjectural Equilibrium in Multiagent Learning
Abstract. Learning in a multiagent environment is complicated by the fact that as other agents learn, the environment effectively changes. Moreover, other agents’ actions are often not directly observable, and the actions taken by the learning agent can strongly bias which range of behaviors are encountered. We define the concept of a conjectural equilibrium, where all agents’ expectations are realized, and each agent responds optimally to its expectations. We present a generic multiagent exchange situation, in which competitive behavior constitutes a conjectural equilibrium. We then introduce an agent that executes a more sophisticated strategic learning strategy, building a model of the response of other agents. We find that the system reliably converges to a conjectural equilibrium, but that the final result achieved is highly sensitive to initial belief. In essence, the strategic learner’s actions tend to fulfill its expectations. Depending on the starting point, the agen...
Michael P. Wellman, Junling Hu
Added 22 Dec 2010
Updated 22 Dec 2010
Type Journal
Year 1998
Where ML
Authors Michael P. Wellman, Junling Hu
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