Policy gradient method for team Markov games

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 3177, Issue , 2004, Pages 733-739

  Könönen, Ville ^a  

^a AALTO UNIVERSITY   (Finland)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 35048903229     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-28651-6_109     Document Type: Article

References (6)

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2. J. Hu and M. P. Wellman. Nash Q-learning for general-sum stochastic games. Journal of Machine Learning Research, 4, 2003.
3. V. J. Könönen. Asymmetric multiagent reinforcement learning. In Proceedings of the 2003 WIC International Conference on Intelligent Agent Technology (IAT-2003), Halifax, Canada, 2003. IEEE Press.
4. V. J. Könönen. Policy gradient method for multiagent reinforcement learning. In Proceedings of the 2nd International Conference on Computational Intelligence, Robotics and Autonomous Systems (CIRAS 2003), Singapore, 2003.
5. L. Peshkin, K.-E. Kim, N. Meuleau, and L. P. Kaelbling. Learning to cooperate via policy-search. In Proceedings of the Sixteenth Conference on Uncertainty in Artifical Intelligence (UAI-2002), Stanford, CA, 2000. Morgan Kaufmann Publishers.
6. R. S. Sutton, D. McAllester, S. Singh, and Y. Mansour. Policy gradient methods for reinforcement learning with function approximation. In Advances in Neural Information Processing Systems, volume 12, Cambridge, MA, 2000. MIT Press.