Abstract
This paper demonstrates the use of pattern-weights in order to develop a strategy for an automated player of a non-cooperative version of the game of Diplomacy. Diplomacy is a multi-player, zero-sum and simultaneous move game with imperfect information. Pattern-weights represent stored knowledge of various aspects of a game that are learned through experience. An automated computer player is developed without any initial strategy and is able to learn important strategic aspects of the game through self-play by storing pattern-weights and using temporal difference learning.
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© 2003 Springer-Verlag Berlin Heidelberg
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Shapiro, A., Fuchs, G., Levinson, R. (2003). Learning a Game Strategy Using Pattern-Weights and Self-play. In: Schaeffer, J., Müller, M., Björnsson, Y. (eds) Computers and Games. CG 2002. Lecture Notes in Computer Science, vol 2883. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-40031-8_4
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DOI: https://doi.org/10.1007/978-3-540-40031-8_4
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-20545-6
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