Learning to Reach the Pareto Optimal Nash Equilibrium as a Team

Author:

Verbeeck Katja,Nowé Ann,Lenaerts Tom,Parent Johan

Publisher

Springer Berlin Heidelberg

Reference12 articles.

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3. Jafari, C., Greenwald, A., Gondek, D. and Ercal, G.: On no-regret learning, fictitious play, and nash equilibrium. Proceedings of the Eighteenth International Conference on Machine Learning, (2001) p 223–226.

4. Lauer, M., Riedmiller, M.: An algorithm for distributed reinforcement learning in cooperative multi-agent systems. Proceedings of the seventeenth International Conference on Machine Learning (2000)

5. Litmann M.L.: Markov games as a framework for multi-agent reinforcement learning. Proceedings of the Eleventh International Conference on Machine Learning, (1994) p 157–163.

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