A View on Deep Reinforcement Learning in Imperfect Information Games
نویسندگان
چکیده
منابع مشابه
Deep Reinforcement Learning from Self-Play in Imperfect-Information Games
Many real-world applications can be described as large-scale games of imperfect information. To deal with these challenging domains, prior work has focused on computing Nash equilibria in a handcrafted abstraction of the domain. In this paper we introduce the first scalable endto-end approach to learning approximate Nash equilibria without any prior knowledge. Our method combines fictitious sel...
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ژورنال
عنوان ژورنال: Studia Universitatis Babeș-Bolyai Informatica
سال: 2020
ISSN: 2065-9601,1224-869X
DOI: 10.24193/subbi.2020.2.03