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- 1Artificial Intelligence
- 1Extensive games
- 1Game Theory
- 1Game theory
- 1Regret minimalization
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2009
Bowling, Michael, Zinkevich, Martin, Waugh, Kevin, Lanctot, Marc
Technical report TR09-15. Sequential decision-making with multiple agents and imperfect information is commonly modeled as an extensive game. One efficient method for computing Nash equilibria in large, zero-sum, imperfect information games is counterfactual regret minimization (CFR). In the...
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2012
Lanctot, Marc, Gibson, Richard, Burch, Neil, Szafron, Duane
In large extensive form games with imperfect information, Counterfactual Regret Minimization (CFR) is a popular, iterative algorithm for computing approximate Nash equilibria. While the base algorithm performs a full tree traversal on each iteration, Monte Carlo CFR (MCCFR) reduces the per...