Multiagent Reinforcement Learning

Author:

How Jonathan P.,Kim Dong-Ki,Wadhwania Samir

Publisher

Springer International Publishing

Reference48 articles.

1. Amir O, Kamar E, Kolobov A, Grosz BJ (2016) Interactive teaching strategies for agent training. In: International joint conferences on artificial intelligence (IJCAI)

2. Avis D, Rosenberg GD, Savani R, von Stengel B (2010) Enumeration of nash equilibria for two-player games. Econ Theory 42(1):9–37. [Online]. Available: https://doi.org/10.1007/s00199-009-0449-x

3. Bowling M (2005) Convergence and no-regret in multiagent learning. In: Saul LK, Weiss Y, Bottou L (eds) Advances in neural information processing systems 17. MIT Press, pp 209–216. [Online]. Available: http://papers.nips.cc/paper/2673-convergen ce-and-no-regret-in-multiagent-learning.pdf

4. Buşoniu L, Babuška R, De Schutter B (2010) Multi-agent reinforcement learning: an overview. Springer, Berlin/Heidelberg, pp 183–221. [Online]. Available: https://doi.org/10.1007/978-3-642-14435-6_7

5. Clouse J (1997) On integrating apprentice learning and reinforcement learning

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