A Comparison between Cognitive and AI Models of Blackjack Strategy Learning

  • Marvin R. G. Schiller
  • Fernand R. Gobet
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7526)


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.


Basic Strategy Cognitive Architecture Iowa Gambling Task Human Player Casino Game 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Marvin R. G. Schiller
    • 1
  • Fernand R. Gobet
    • 1
  1. 1.Brunel UniversityLondonUK

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