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A model of expert decision making in post-flop betting in poker

  • University of Toronto

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

Most past research in modelling poker arises from the field of artificial intelligence, based on the many rules and probabilities involved in the game. The present study examines poker from a new perspective: applying knowledge elicitation techniques to model some of the decision making processes of expert poker players in post-flop betting. Based on data obtained through observations and interviews, using expert players as study participants, a decision making model is proposed, together with an abstraction hierarchy model. It was found that poker players create a set of mental models of their opponents, the active game situation, and of themselves as perceived by their opponents, in order to achieve the purposes of always making better decisions than their opponent and, whenever possible, maximizing the consequences of the opponent's mistakes. A set of strategies that are independent of specific situations and individual players were also discovered in this study.

Original languageEnglish
Title of host publication52nd Human Factors and Ergonomics Society Annual Meeting, HFES 2008
Pages433-437
Number of pages5
StatePublished - 2008
Event52nd Human Factors and Ergonomics Society Annual Meeting, HFES 2008 - New York, NY, United States
Duration: Sep 22 2008Sep 26 2008

Publication series

NameProceedings of the Human Factors and Ergonomics Society
Volume1
ISSN (Print)1071-1813

Conference

Conference52nd Human Factors and Ergonomics Society Annual Meeting, HFES 2008
Country/TerritoryUnited States
CityNew York, NY
Period09/22/0809/26/08

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