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首页> 外文会议>The 2014 IEEE/WIC/ACM International Conference on Intelligent Agent Technology >A Profitable Online No-Limit Poker Playing Agent
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A Profitable Online No-Limit Poker Playing Agent

机译：一个赚钱的在线无限额扑克玩家

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摘要

The No-Limit Texas Hold'em variant of Poker is the game that is most frequently used to assess new developments in incomplete information problems, through the development of game playing agents. For this particular game, current state-of-the-art techniques consist in the pre-computation of a set of strategies that are in a Nash-Equilibrium state. However, due to the game's decision tree size, current algorithms only work in an abstracted version of No-Limit Poker. Moreover, since these strategies are static, they ignore the opponents' playing style thus being unable to maximize profit against certain kinds of opponents. This makes these strategies unusable when playing in an online environment against human players. In this paper we present a rule-based strategy approach for a No-Limit Poker agent that was developed to play online, against human players and in online multiplayer matches. This strategy is based on a popular technique used by human players - short stack playing - which consists of playing in tables with up to 6 players and low initial resources. Using domain specific opponent modeling techniques and limiting the decisions to the first round of the game, the agent was able to make a good profit margin of 11.5% per game when playing against human players. The significance of our results resides in the fact that, for the first time in the Computer Poker literature, we present a game playing agent that can match human players in multiplayer games.
机译：扑克的无限德州德州扑克变种是最常用于通过开发游戏代理来评估不完全信息问题的新发展的游戏。对于此特定游戏，当前的最新技术包括对处于Nash平衡状态的一组策略进行预计算。但是，由于游戏的决策树大小，当前算法仅适用于无限额扑克的抽象版本。而且，由于这些策略是静态的，因此它们忽略了对手的游戏风格，因此无法最大化地对抗某些类型的对手的利润。这使得这些策略在在线环境中与人类玩家对抗时无法使用。在本文中，我们为无限制扑克代理提供了一种基于规则的策略方法，该代理被开发为在线玩，对抗人类玩家和在线多人游戏。此策略基于人类玩家使用的一种流行技术-短筹码游戏-包括在最多6名玩家和低初始资源的牌桌上进行游戏。通过使用特定领域的对手建模技术并将决策限制在游戏的第一轮，当与人类玩家对战时，该代理商能够获得每场游戏11.5％的良好利润率。我们的结果的意义在于，在计算机扑克文献中，我们首次提出了一种可以在多人游戏中与人类玩家匹敌的游戏代理。

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