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Evaluating agent performance when outcomes are stochastic and agents use randomized strategies can be challenging when there is limited data available.
Zur theorie der gesellschaftsspiele
J. von Neumann · 1928
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Representations and solutions for game-theoretic problems
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The challenge of poker
Darse Billings, Aaaron Davidson, Jonathen Schaeffer, and Duane Szafron · 2002
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Approximating game-theoretic optimal strategies for full-scale poker
Darse Billings, Neil Burch, Aaaron Davidson, Robert Holte, Jonathan Schaeffer, Terence Schauenberg, and Duane Szafron · 2003
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Bayes’ bluff: Opponent modelling in poker
Finnegan Southey, Michael H. Bowling, Bryce Larson, Carmelo Piccione, Neil Burch, Darse Billings, and D. Chris Rayner · 2005
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The AAAI computer poker competition
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Optimal unbiased estimators for evaluating agent performance
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The Economist
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website, http://www.computerpokercompetition.org/
Annual Computer Poker Competition
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Learning a value analysis tool for agent evaluation
Martha White and Michael H. Bowling · 2009
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Potential-aware imperfect-recall abstraction with earth mover’s distance in imperfect-information games
Sam Ganzfried and Tuomas Sandholm · 2014
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http://www.cs.cmu.edu/brains-vs-ai, 2015
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Doug polk and team beat claudico to win $100,000 from microsoft & the rivers casino
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