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Learning Multi-agent Strategies in Multi-stage Collaborative Games

  • W. Andy Wright
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2412)

Abstract

An alternative approach to learning decision strategies in multi-state multiple agent systems is presented here. The method, which uses a game theoretic construction which is model free and does not rely on direct communication between the agents in the system. Limited experiments show that the method can find Nash equilibrium point for 3 player multi-stage game and converges more quickly than a comparable co-evolution method.

Keywords

Nash Equilibrium Reinforcement Learning Mixed Strategy Pure Strategy Independent Learner 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • W. Andy Wright
    • 1
    • 2
  1. 1.BAE SYSTEMS (ATC)BristolUK
  2. 2.Department of MathematicsUniversity of BristolBristol

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