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References
Michael Bowling and Manuela Veloso. Multiagent learning using a variable learning rate. Artificial Intelligence, 136:215-250, 2002.
Michael H. Bowling and Manuela M. Veloso. Rational and convergent learning in stochastic games. In Proc. of IJCAI 2001, pages 1021-1026, 2001.
David Carmel and Shaul Markovitch. Exploration strategies for model-based learning in multiagent systems. Autonomous Agents and Multi-agent Systems, 2:141-172, 1999.
Andrew Garland and Richard Alterman. Learning procedural knowledge to better coordinate. In Proc. of the Seventeenth International Joint Conference on Artificial Intelligence, pages 1073-1079. IJCAI, 2001.
Maozu Guo, Yang Liu, and J. Malec. A new q-learning algorithm based on the metropolis criterion. IEEE Transactions on Systems, Man and Cybernetics, Part B, 34(5):2140-2143, Oct. 2004.
Franziska Kluegl, Ana L. C. Bazzan, and Joachim Wahle. Selection of information types based on personal utility - a testbed for traffic information markets. In Proc. of the Second International Joint Conference on Autonomous Agents and Milti Agent Systems, pages 377-384. AAMAS, 2003.
Masayuki Ohta and Itsuki Noda. Reduction of adverse effect of globalinformation on selfish agents. In Luis Antunes and Keiki Takadama, editors, Seventh International Workshop on Multi-Agent-Based Simulation (MABS), pages 7-16, Hakodate, May 2006. AAMAS-2006. Shinko.
Bob Price and Craig Boutilier. Accelerating reinforcement learning through implicit imitation. Journal of Artificial Intelligence Research, 19:569-629, 2003.
Ming Tan. Multi-agent reinforcement learning: Independent vs. cooperative agents. In Proc. of the Tenth International Conference on Machine Learning, pages 330-337, 1993.
David H. Wolpert, Kagan Tumer, and Jeremy Frank. Using collective intelligence to route internet traffic. Advances in Neural Information Processing Systems, 11:952-958, 1999.
Tomohisa Yamashita, Kiyoshi Izumi, Koichi Kurumatani, and Hideyuki Nakashima. Smooth traffic flow with a cooperative car navigation system. In Proc. of the Fourth International Joint Conference on Autonomous Agents and Milti Agent Systems, pages 478-485. AAMAS, 2005.
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Noda, I., Ohta, M. (2007). How to Form Stable and Robust Network Structure through Agent Learning—from the viewpoint of a resource sharing problem. In: Namatame, A., Kurihara, S., Nakashima, H. (eds) Emergent Intelligence of Networked Agents. Studies in Computational Intelligence, vol 56. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71075-2_15
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DOI: https://doi.org/10.1007/978-3-540-71075-2_15
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