{"title":"德州扑克的统计开发模块:当与近似纳什均衡策略一起使用时,它的好处","authors":"Kevin Norris, I. Watson","doi":"10.1109/CIG.2013.6633614","DOIUrl":null,"url":null,"abstract":"An approximate Nash equilibrium strategy is difficult for opponents of all skill levels to exploit, but it is not able to exploit opponents. Opponent modeling strategies on the other hand provide the ability to exploit weak players, but have the disadvantage of being exploitable to strong players. We examine the effects of combining an approximate Nash equilibrium strategy with an opponent based strategy. We present a statistical exploitation module that is capable of adding opponent based exploitation to any base strategy for playing No Limit Texas Hold'em. This module is built to recognize statistical anomalies in the opponent's play and capitalize on them through the use of expert designed statistical exploitations. Expert designed statistical exploitations ensure that the addition of the module does not increase the exploitability of the base strategy. The merging of an approximate Nash equilibrium strategy with the statistical exploitation module has shown promising results in our initial experiments against a range of static opponents with varying exploitabilities. It could lead to a champion level player once the module is improved to deal with dynamic opponents.","PeriodicalId":158902,"journal":{"name":"2013 IEEE Conference on Computational Inteligence in Games (CIG)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"A statistical exploitation module for Texas Hold'em: And it's benefits when used with an approximate nash equilibrium strategy\",\"authors\":\"Kevin Norris, I. Watson\",\"doi\":\"10.1109/CIG.2013.6633614\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An approximate Nash equilibrium strategy is difficult for opponents of all skill levels to exploit, but it is not able to exploit opponents. Opponent modeling strategies on the other hand provide the ability to exploit weak players, but have the disadvantage of being exploitable to strong players. We examine the effects of combining an approximate Nash equilibrium strategy with an opponent based strategy. We present a statistical exploitation module that is capable of adding opponent based exploitation to any base strategy for playing No Limit Texas Hold'em. This module is built to recognize statistical anomalies in the opponent's play and capitalize on them through the use of expert designed statistical exploitations. Expert designed statistical exploitations ensure that the addition of the module does not increase the exploitability of the base strategy. The merging of an approximate Nash equilibrium strategy with the statistical exploitation module has shown promising results in our initial experiments against a range of static opponents with varying exploitabilities. It could lead to a champion level player once the module is improved to deal with dynamic opponents.\",\"PeriodicalId\":158902,\"journal\":{\"name\":\"2013 IEEE Conference on Computational Inteligence in Games (CIG)\",\"volume\":\"22 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-10-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 IEEE Conference on Computational Inteligence in Games (CIG)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CIG.2013.6633614\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE Conference on Computational Inteligence in Games (CIG)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIG.2013.6633614","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A statistical exploitation module for Texas Hold'em: And it's benefits when used with an approximate nash equilibrium strategy
An approximate Nash equilibrium strategy is difficult for opponents of all skill levels to exploit, but it is not able to exploit opponents. Opponent modeling strategies on the other hand provide the ability to exploit weak players, but have the disadvantage of being exploitable to strong players. We examine the effects of combining an approximate Nash equilibrium strategy with an opponent based strategy. We present a statistical exploitation module that is capable of adding opponent based exploitation to any base strategy for playing No Limit Texas Hold'em. This module is built to recognize statistical anomalies in the opponent's play and capitalize on them through the use of expert designed statistical exploitations. Expert designed statistical exploitations ensure that the addition of the module does not increase the exploitability of the base strategy. The merging of an approximate Nash equilibrium strategy with the statistical exploitation module has shown promising results in our initial experiments against a range of static opponents with varying exploitabilities. It could lead to a champion level player once the module is improved to deal with dynamic opponents.