- Title
- Using stereotypes to improve early-match poker play
- Creator
- Layton, Robert; Vamplew, Peter; Turville, Christopher
- Date
- 2008
- Type
- Text; Journal article
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/65173
- Identifier
- vital:1708
- Identifier
-
https://doi.org/10.1007/978-3-540-89378-3_59
- Identifier
- ISSN:0302-9743
- Abstract
- Agent modelling is a critical aspect of many artificial intelligence systems. Many different techniques are used to learn the tendencies of another agent, though most suffer from a slow learning time. The research proposed in this paper examines stereotyping as a method to improve the learning time of poker playing agents. Poker is a difficult domain for opponent modelling due to its hidden information, stochastic elements and complex strategies. However, the literature suggests there are clusters of similar poker strategies, making it an ideal environment to test the effectiveness of stereotyping. This paper presents a method for using stereotyping in a poker bot, and shows that stereotyping improves performance in early-match play in many scenarios. © 2008 Springer Berlin Heidelberg.
- Publisher
- Auckland Springer
- Relation
- Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 5360 LNAI, no. (1 December 2008 through 5 December 2008 2008), p. 584-593
- Rights
- Copyright Springer
- Rights
- This metadata is freely available under a CCO license
- Subject
- Agent modelling; Games; Opponent modelling; Poker; Stereotypes
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