Abstract
A Case-Based Reasoning system, nicknamed SARTRE, that uses a memory-based approach to play two-player, limit Texas Hold’em is introduced. SARTRE records hand histories from strong players and attempts to re-use this information to handle novel situations. SARTRE’S case features and their representations are described, followed by the results obtained when challenging a world-class computerised opponent. Our experimental methodology attempts to address how well SARTRE’S performance can approximate the performance of the expert player, who SARTRE originally derived the experience-base from.
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Rubin, J., Watson, I. (2009). A Memory-Based Approach to Two-Player Texas Hold’em. In: Nicholson, A., Li, X. (eds) AI 2009: Advances in Artificial Intelligence. AI 2009. Lecture Notes in Computer Science(), vol 5866. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10439-8_47
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DOI: https://doi.org/10.1007/978-3-642-10439-8_47
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-10438-1
Online ISBN: 978-3-642-10439-8
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