The State of Solving Large Incomplete-Information Games, and Application to Poker
AbstractGame-theoretic solution concepts prescribe how rational parties should act, but to become operational the concepts need to be accompanied by algorithms. I will review the state of solving incomplete-information games. They encompass many practical problems such as auctions, negotiations, and security applications. I will discuss them in the context of how they have transformed computer poker. In short, game-theoretic reasoning now scales to many large problems, outperforms the alternatives on those problems, and in some games beats the best humans.
How to Cite
Sandholm, T. (2010). The State of Solving Large Incomplete-Information Games, and Application to Poker. AI Magazine, 31(4), 13-32. https://doi.org/10.1609/aimag.v31i4.2311
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