Deep Reinforcement Learning from Self-Play in No-limit Texas Hold'em Poker

Imperfect information games describe many practical applications found in the real world as the information space is rarely fully available. This particular set of problems is challenging due to the random factor that makes even adaptive methods fail to correctly model the problem and find the best...

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Vydané v:	Studia Universitatis Babes-Bolyai: Series Informatica Ročník 66; číslo 2; s. 51
Hlavný autor:	Pricope, T.-V.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Babes-Bolyai University, Cluj-Napoca 15.12.2021
Predmet:	Artificial Intelligence, Computer Poker, Adaptive Learning, Fictitious Play, Self-Play, Deep Reinforcement Learning, Neural Networks
ISSN:	1224-869X, 2065-9601
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