ML Anthology

Bayes-Relational Learning of Opponent Models from Incomplete Information in No-Limit Poker

Marc J. V. Ponsen, Jan Ramon, Tom Croonenborghs, Kurt Driessens, Karl Tuyls
AAAI 2008 pp. 1485-1486
/aaai/2008/ponsen2008aaai-bayes/

Abstract

We propose an opponent modeling approach for No-Limit Texas Hold'em poker that starts from a (learned) prior, i.e., general expectations about opponent behavior and learns a relational regression tree-function that adapts these priors to specific opponents. An important asset is that this approach can learn from incomplete information (i.e. without knowing all players' hands in training games).

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Cite

Text

Ponsen et al. "Bayes-Relational Learning of Opponent Models from Incomplete Information in No-Limit Poker." AAAI Conference on Artificial Intelligence, 2008.

Markdown

[Ponsen et al. "Bayes-Relational Learning of Opponent Models from Incomplete Information in No-Limit Poker." AAAI Conference on Artificial Intelligence, 2008.](https://mlanthology.org/aaai/2008/ponsen2008aaai-bayes/)

BibTeX

@inproceedings{ponsen2008aaai-bayes,
  title     = {{Bayes-Relational Learning of Opponent Models from Incomplete Information in No-Limit Poker}},
  author    = {Ponsen, Marc J. V. and Ramon, Jan and Croonenborghs, Tom and Driessens, Kurt and Tuyls, Karl},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2008},
  pages     = {1485-1486},
  url       = {https://mlanthology.org/aaai/2008/ponsen2008aaai-bayes/}
}