Abstract
An action selection method based on the estimation of other’s intention is proposed to treat with time-varying multi-agent environments. Firstly, the estimation level of other’s intention is stratified as active, passive and thoughtful levels. Secondly, three estimation levels are formulated by a policy estimation method. Thirdly, a new action selection method by switching three estimation levels is proposed to cope with time-varying environments. Fourthly, the estimation methods of other’s intention are applied to the Q-learning method. Finally, through computer simulations using pursuit problems, the performance of the estimation methods are investigated. As a result, it is shown that the proposed method can select the appropriate estimation level in time-varying environments.
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References
Stone, P., Veloso, M.: Multiagent Systems: A Survey from a Machine Learning Perspective. Autonomous Robots 8(3), 345–383 (2000)
Kaelbling, L.P., Littman, M.L., Moore, A.P.: Reinforcement Learning: A Survey. Journal of Artificial Intelligence Research 4, 237–285 (1996)
Sutton, R.S., Barto, A.G.: Reinforcement Learning: An Introduction. MIT Press (1998)
Bratman, M.E.: Intention, Plans and Practical Reason. Harvard University Press (1987)
Nagayuki, Y., Ishii, S., Ito, M., Shimohara, K., Doya, K.: A Multi-Agent Reinforcement Learning Method with the Estimation of the Other Agent’s Actions. In: Proceedings of the Fifth International Symposium on Artificial Life and Robotics, vol. 1, pp. 255–259 (2000)
Nagayuki, Y., Ito, M.: Reinforcement Learning Method with the Inference of the Other Agent’s Policy for 2-Player Stochastic Games. Transactions on the Institute of Electronics, Information and Communication Engineers J86-D-I(11), 821–829 (2003) (in Japanese)
Watkins, C.J.C.H., Dayan, P.: Q-learning. Machine Learning 8(3-4), 279–292 (1992)
Yokoyama, A., Omori, T., Ishikawa, S., Okada, H.: Modeling of Action Decision Process Based on Intention Estimation. In: Proceedings of Joint 4th International Conference on Soft Computing and Intelligent Systems and 9th International Symposium on advanced Intelligent Systems, vol. TH-F3-1 (2008)
Yokoyama, A., Omori, T.: Model Based Analysis of Action Decision Process in Collaborative Task Based on Intention Estimation. Transactions on the Institute of Electronics, Information and Communication Engineers J92-A(11), 734–742 (2009)
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Kobayashi, K., Kanehira, R., Kuremoto, T., Obayashi, M. (2011). An Action Selection Method Based on Estimation of Other’s Intention in Time-Varying Multi-agent Environments. In: Lu, BL., Zhang, L., Kwok, J. (eds) Neural Information Processing. ICONIP 2011. Lecture Notes in Computer Science, vol 7064. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24965-5_9
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DOI: https://doi.org/10.1007/978-3-642-24965-5_9
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