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We present new approximation methods for computing gametheoretic strategies for sequential games of imperfect information. At a high level, we contribute two new ideas. First, we introduce a new state-space abstraction algorithm. In each round of the game, there is a limit to the number of strategically different situations that an equilibrium-finding algorithm can handle. Given this constraint, we use clustering to discover similar positions, and we compute the abstraction via an integerdoi:10.1145/1329125.1329358 dblp:conf/atal/GilpinS07 fatcat:ebuxhjl3z5gnddhxxf7rzwt4ne