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References

1
Sachiyo Arai, Kazuteru Miyazaki, and Shigenobu Kobayashi. Generating cooperative behavior by multi-agent reinforcement learning. In Sixth European Workshop on Learning Robots, Brighton, UK, August 1997.

2
Minoru Asada, Shoichi Noda, Sukoya Tawaratumida, and Koh Hosoda. Purposive behavior acquisition for a real robot by vision-based reinforcement learning. Machine Learning, 23:279-303, 1996.

3
J. A. Boyan and M. L. Littman. Packet routing in dynamically changing networks: A reinforcement learning approach. In J. D. Cowan, G. Tesauro, and J. Alspector, editors, Advances In Neural Information Processing Systems 6. Morgan Kaufmann Publishers, 1994.

4
Leslie Pack Kaelbling, Anthony R. Cassandra, and Michael L. Littman. Acting optimally in partially observable stochastic domains. In Proceedings of the Twelfth National Conference on Artificial Intelligence, 1994.

5
Leslie Pack Kaelbling, Michael L. Littman, and Andrew W. Moore. Reinforcement learning: A survey. Journal of Artificial Intelligence Research, 4:237-285, May 1996.

6
Hiroaki Kitano, Yasuo Kuniyoshi, Itsuki Noda, Minoru Asada, Hitoshi Matsubara, and Eiichi Osawa. RoboCup: A challenge problem for AI. AI Magazine, 18(1):73-85, Spring 1997.

7
Michael L. Littman. Markov games as a framework for multi-agent reinforcement learning. In Proceedings of the Eleventh International Conference on Machine Learning, pages 157-163, San Mateo, CA, 1994. Morgan Kaufman.

8
Sean Luke, Charles Hohn, Jonathan Farris, Gary Jackson, and James Hendler. Co-evolving soccer softbot team coordination with genetic programming. In Hiroaki Kitano, editor, RoboCup-97: The First Robot World Cup Soccer Games and Conferences, Berlin, 1998. Springer Verlag. In Press.

9
Maja J. Mataric. Interaction and intelligent behavior. MIT EECS PhD Thesis AITR-1495, MIT AI Lab, August 1994.

10
Itsuki Noda, Hitoshi Matsubara, and Kazuo Hiraki. Learning cooperative behavior in multi-agent environment: a case study of choice of play-plans in soccer. In PRICAI'96: Topics in Artificial Intelligence (Proc. of 4th Pacific Rim International Conference on Artificial Intelligence, Cairns, Australia), pages 570-579, Cairns,Australia, August 1996.

11
J. Ross Quinlan. C4.5: Programs for Machine Learning. Morgan Kaufmann, San Mateo, CA, 1993.

12
Rafal P. Salustowicz, Marco A. Wiering, and Jurgen Schmidhuber. Learning team strategies: Soccer case studies. Machine Learning, 1998. To appear.

13
Peter Stone and Manuela Veloso. Multiagent systems: A survey from a machine learning perspective. Technical Report CMU-CS-97-193, Computer Science Department, Carnegie Mellon University, Pittsburgh, PA, December 1997.

14
Peter Stone and Manuela Veloso. A layered approach to learning client behaviors in the RoboCup soccer server. Applied Artificial Intelligence, 12, 1998. In Press.

15
Peter Stone and Manuela Veloso. Towards collaborative and adversarial learning: A case study in robotic soccer. International Journal of Human-Computer Systems, 48, 1998. In Press.

16
Peter Stone and Manuela Veloso. Using decision tree confidence factors for multiagent control. In Hiroaki Kitano, editor, RoboCup-97: The First Robot World Cup Soccer Games and Conferences. Springer Verlag, Berlin, 1998. In Press.

17
Ming Tan. Multi-agent reinforcement learning: Independent vs. cooperative agents. In Proceedings of the Tenth International Conference on Machine Learning, pages 330-337, 1993.

18
Manuela Veloso, Peter Stone, Kwun Han, and Sorin Achim. The CMUnited-97 small-robot team. In Hiroaki Kitano, editor, RoboCup-97: The First Robot World Cup Soccer Games and Conferences. Springer Verlag, Berlin, 1998.

19
Jieyu Zhao and Jurgen Schmidhuber. Incremental self-improvement for life-time multi-agent reinforcement learning. In Proceedings of the 4th International Conference of Simulation of Adaptive Behaviros (SAB 4), pages 363-372. MIT Press, 1996.



Peter Stone
Fri Feb 27 18:45:43 EST 1998