Open AccessThe State of Solving Large Incomplete‐Information Games, and Application to Poker
Author(s) -
Sandholm Tuomas
Publication year - 2010
Publication title -
ai magazine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.597
H-Index - 79
eISSN - 2371-9621
pISSN - 0738-4602
DOI - 10.1609/aimag.v31i4.2311
Subject(s) - computer science , complete information , negotiation , state (computer science) , common value auction , context (archaeology) , game theory , sequential game , management science , mathematical economics , algorithm , mathematics , engineering , microeconomics , economics , paleontology , political science , law , biology
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.