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By Vedran Kordic

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Extra resources for Autonomous Agents

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Stone, P. (2007). Transfer via inter-task mappings in policy search reinforcement learning. Proceedings of the Sixth International Conference on Autonomous Agents and Multiagent Systems. Tracking behaviours of cooperative robots within multi-agent domains 45 X3 Tracking behaviours of cooperative robots within multi-agent domains Fernando Ramos1 and Huberto Ayanegui2 1Tecnologico de Monterrey Campus Cuernavaca Autónoma de Tlaxcala Mexico 2Universidad 1. Introduction The most important concerns in multi-agent cooperative systems are focused on the construction of models related with the communication, the interaction and the behavior of agents participating in a task.

318–325. Claus, C. & Boutilier, C. (1998). The dynamics of reinforcement learning in cooperative multiagent systems, National Conference on Artificial Intelligence (AAAI), pp. 746–752. Cohen, P. R. (1995). Empirical Methods for Artificial Intelligence, MIT Press, Cambridge, MA, USA. Crites, R. H. & Barto, A. G. (1998). Elevator group control using multiple reinforcement learning agents, Machine Learning 33(2): 235–262. de Oliveira, L. , Bortolozzi, F. & Suen, C. Y. (2003). A methodology for feature selection using multiobjective genetic algorithms for handwritten digit string recognition, International Journal of Pattern Recognition and Artificial Intelligence 17(6): 903– 929.

Reinforcement Learning for the Adaptive Control of Perception and Action, PhD thesis, University of Rochester. Yang, J. & Honavar, V. (1998). Feature subset selection using a genetic algorithm, IEEE Intelligent Systems and Their Applications 13(2): 44–49. 26 Autonomous Agents Graph Laplacian Based Transfer Learning Methods in Reinforcement Learning 27 X2 Graph Laplacian Based Transfer Learning Methods in Reinforcement Learning Yi-Ting Tsao, Ke-Ting Xiao, Von-Wun Soo and Chung-Cheng Chiu Department of Computer Science, National Tsing Hua University HsinChu, Taiwan 1.

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