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Combining Incremental Strategy Generation and Branch and Bound Search for Computing Maxmin Strategies in Imperfect Recall Games.

, , and . AAMAS, page 902-910. ACM, (2017)

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Algorithms for computing strategies in two-player simultaneous move games., , , , and . Artif. Intell., (2016)Combining Incremental Strategy Generation and Branch and Bound Search for Computing Maxmin Strategies in Imperfect Recall Games., , and . AAMAS, page 902-910. ACM, (2017)Automated Construction of Bounded-Loss Imperfect-Recall Abstractions in Extensive-Form Games (Extended Abstract)., , and . IJCAI, page 5030-5034. ijcai.org, (2020)Journal track.Solving Imperfect Recall Games.. AAMAS, page 1820-1821. ACM, (2017)Strategy Effectiveness of Game-Theoretical Solution Concepts in Extensive-Form General-Sum Games., , and . AAMAS, page 1813-1814. ACM, (2015)Automated construction of bounded-loss imperfect-recall abstractions in extensive-form games., , and . Artif. Intell., (2020)Practical Performance of Refinements of Nash Equilibria in Extensive-Form Zero-Sum Games., , and . ECAI, volume 263 of Frontiers in Artificial Intelligence and Applications, page 201-206. IOS Press, (2014)Towards Solving Imperfect Recall Games., and . AAAI Workshops, volume WS-17 of AAAI Technical Report, AAAI Press, (2017)An Algorithm for Constructing and Solving Imperfect Recall Abstractions of Large Extensive-Form Games., , and . IJCAI, page 936-942. ijcai.org, (2017)Learning with proxy supervision for end-to-end visual learning., and . Intelligent Vehicles Symposium, page 1-6. IEEE, (2017)