Computing card probabilities in Texas Hold'em
Main Author: | |
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Publication Date: | 2013 |
Other Authors: | , |
Format: | Book |
Language: | eng |
Source: | Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
Download full: | https://hdl.handle.net/10216/67093 |
Summary: | Developing Poker agents that can compete at the level of a human expert can be a challenging endeavor, since agents' strategies must be capable of dealing with hidden information, deception and risk management. A way of addressing this issue is to model opponents' behavior in order to estimate their game plan and make decisions based on such estimations. In this paper, several hand evaluation and classification techniques are compared and conclusions on their respective applicability and scope are drawn. Also, we suggest improvements on current techniques through Monte Carlo sampling. The current methods to deal with risk management were found to be pertinent concerning the agent's decision-making process; nevertheless future integration of these methods with opponent modeling techniques can greatly improve overall Poker agents' performance. |
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Computing card probabilities in Texas Hold'emEngenharia electrotécnica, electrónica e informáticaElectrical engineering, Electronic engineering, Information engineeringDeveloping Poker agents that can compete at the level of a human expert can be a challenging endeavor, since agents' strategies must be capable of dealing with hidden information, deception and risk management. A way of addressing this issue is to model opponents' behavior in order to estimate their game plan and make decisions based on such estimations. In this paper, several hand evaluation and classification techniques are compared and conclusions on their respective applicability and scope are drawn. Also, we suggest improvements on current techniques through Monte Carlo sampling. The current methods to deal with risk management were found to be pertinent concerning the agent's decision-making process; nevertheless future integration of these methods with opponent modeling techniques can greatly improve overall Poker agents' performance.20132013-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/bookapplication/pdfhttps://hdl.handle.net/10216/67093engLuís Filipe TeófiloLuís Paulo ReisHenrique Lopes Cardosoinfo:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2025-02-27T16:56:07Zoai:repositorio-aberto.up.pt:10216/67093Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T21:57:46.676684Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse |
dc.title.none.fl_str_mv |
Computing card probabilities in Texas Hold'em |
title |
Computing card probabilities in Texas Hold'em |
spellingShingle |
Computing card probabilities in Texas Hold'em Luís Filipe Teófilo Engenharia electrotécnica, electrónica e informática Electrical engineering, Electronic engineering, Information engineering |
title_short |
Computing card probabilities in Texas Hold'em |
title_full |
Computing card probabilities in Texas Hold'em |
title_fullStr |
Computing card probabilities in Texas Hold'em |
title_full_unstemmed |
Computing card probabilities in Texas Hold'em |
title_sort |
Computing card probabilities in Texas Hold'em |
author |
Luís Filipe Teófilo |
author_facet |
Luís Filipe Teófilo Luís Paulo Reis Henrique Lopes Cardoso |
author_role |
author |
author2 |
Luís Paulo Reis Henrique Lopes Cardoso |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Luís Filipe Teófilo Luís Paulo Reis Henrique Lopes Cardoso |
dc.subject.por.fl_str_mv |
Engenharia electrotécnica, electrónica e informática Electrical engineering, Electronic engineering, Information engineering |
topic |
Engenharia electrotécnica, electrónica e informática Electrical engineering, Electronic engineering, Information engineering |
description |
Developing Poker agents that can compete at the level of a human expert can be a challenging endeavor, since agents' strategies must be capable of dealing with hidden information, deception and risk management. A way of addressing this issue is to model opponents' behavior in order to estimate their game plan and make decisions based on such estimations. In this paper, several hand evaluation and classification techniques are compared and conclusions on their respective applicability and scope are drawn. Also, we suggest improvements on current techniques through Monte Carlo sampling. The current methods to deal with risk management were found to be pertinent concerning the agent's decision-making process; nevertheless future integration of these methods with opponent modeling techniques can greatly improve overall Poker agents' performance. |
publishDate |
2013 |
dc.date.none.fl_str_mv |
2013 2013-01-01T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/book |
format |
book |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://hdl.handle.net/10216/67093 |
url |
https://hdl.handle.net/10216/67093 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
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openAccess |
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application/pdf |
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Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
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Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia |
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