The State of Solving Large Incomplete-Information Games, and Application to Poker

  • Tuomas Sandholm Carnegie Mellon University

Abstract

Game-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.
Published
2010-09-25
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
Section
Articles