CFR-D: Solving Imperfect Information Games Using Decomposition
نویسندگان
چکیده
One of the significant advantages in problems with perfect information, like search or games like checkers, is that they can be decomposed into independent pieces. In contrast, problems with imperfect information, like market modeling or games like poker, are treated as a single decomposable whole. Handling the game as a single unit places a much stricter limit on the size of solvable imperfect information games. This paper has two main contributions. First, we introduce CFR-D, a new variant of the counterfactual regret minimising family of algorithms. For any problem which can be decomposed into a trunk and subproblems, CFR-D can handle the trunk and each subproblem independently. Decomposition lets CFR-D have memory requirements which are sub-linear in the number of decision points, a desirable property more commonly associated with perfect information algorithms. Second, we present an algorithm for recovering an equilibrium strategy in a subproblem given the trunk strategy and some summary information about the subproblem.
منابع مشابه
Solving Imperfect Information Games Using Decomposition
Decomposition, i.e., independently analyzing possible subgames, has proven to be an essential principle for effective decision-making in perfect information games. However, in imperfect information games, decomposition has proven to be problematic. To date, all proposed techniques for decomposition in imperfect information games have abandoned theoretical guarantees. This work presents the firs...
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ورودعنوان ژورنال:
- CoRR
دوره abs/1303.4441 شماره
صفحات -
تاریخ انتشار 2013