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A comparison between cognitive and AI models of blackjack strategy learning

Schiller, Marvin R.G. and Gobet, Fernand R. ORCID: 0000-0002-9317-6886 (2012) A comparison between cognitive and AI models of blackjack strategy learning. In: Glimm, Birte and Krüger, Antonio, (eds.) KI 2012: Advances in Artificial Intelligence - 35th Annual German Conference on AI, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer Berlin / Heidelberg, Saarbrücken, DE, 143 - 155. ISBN 9783642333460

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Identification Number: 10.1007/978-3-642-33347-7_13


Cognitive models of blackjack playing are presented and investigated. Blackjack playing is considered a useful test case for theories on human learning. Curiously, despite the existence of a relatively simple, well-known and optimal strategy for blackjack, empirical studies have found that casino players play quite differently from that strategy. The computational models presented here attempt to explain this result by modelling blackjack playing using the cognitive architecture CHREST. Two approaches to modeling are investigated and compared; (i) the combination of classical and operant conditioning, as studied in psychology, and (ii) SARSA, as studied in AI.

Item Type: Book Section
Official URL:
Additional Information: © 2012 Springer-Verlag Berlin Heidelberg
Divisions: CPNSS
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
B Philosophy. Psychology. Religion > B Philosophy (General)
Date Deposited: 10 Dec 2019 10:06
Last Modified: 18 Jul 2024 06:24

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