An Approach of Solving Early Phase Multiplayer No-Limit Hold'em Poker
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Most Important Fundamental Rule of Poker Strategy
The Thirty-Third International FLAIRS Conference (FLAIRS-33) Most Important Fundamental Rule of Poker Strategy Sam Ganzfried,1 Max Chiswick 1Ganzfried Research Abstract start playing very quickly, even the best experts spend many years (for some an entire lifetime) learning and improving. Poker is a large complex game of imperfect information, Humans learn and improve in a variety of ways. The most which has been singled out as a major AI challenge prob- obvious are reading books, hiring coaches, poker forums and lem. Recently there has been a series of breakthroughs culmi- nating in agents that have successfully defeated the strongest discussions, and simply playing a lot to practice. Recently human players in two-player no-limit Texas hold ’em. The several popular software tools have been developed, most 1 strongest agents are based on algorithms for approximating notably PioSolver, where players solve for certain situa- Nash equilibrium strategies, which are stored in massive bi- tions, given assumptions for the hands the player and oppo- nary files and unintelligible to humans. A recent line of re- nent can have. This is based on the new concept of endgame search has explored approaches for extrapolating knowledge solving (Ganzfried and Sandholm 2015), where strategies from strong game-theoretic strategies that can be understood are computed for the latter portion of the game given fixed by humans. This would be useful when humans are the ulti- strategies for the trunk (which are input by the user). While mate decision maker and allow humans to make better deci- it has been pointed out that theoretically this approach is sions from massive algorithmically-generated strategies. -
Texas Hold'em Poker
11/5/2018 Rules of Card Games: Texas Hold'em Poker Pagat Poker Poker Rules Poker Variants Home Page > Poker > Variations > Texas Hold'em DE EN Choose your language Texas Hold'em Introduction Players and Cards The Deal and Betting The Showdown Strategy Variations Pineapple ‑ Crazy Pineapple ‑ Crazy Pineapple Hi‑Lo Irish Casino Versions Introduction Texas Hold'em is a shared card poker game. Each player is dealt two private cards and there are five face up shared (or "community") cards on the table that can be used by anyone. In the showdown the winner is the player who can make the best five‑card poker hand from the seven cards available. Since the 1990's, Texas Hold'em has become one of the most popular poker games worldwide. Its spread has been helped firstly by a number of well publicised televised tournaments such as the World Series of Poker and secondly by its success as an online game. For many people nowadays, poker has become synonymous with Texas Hold'em. This page assumes some familiarity with the general rules and terminology of poker. See the poker rules page for an introduction to these, and the poker betting and poker hand ranking pages for further details. Players and Cards From two to ten players can take part. In theory more could play, but the game would become unwieldy. A standard international 52‑card pack is used. The Deal and Betting Texas Hold'em is usually played with no ante, but with blinds. When there are more than two players, the player to dealer's left places a small blind, and the next player to the left a big blind. -
Abiding Chance: Online Poker and the Software of Self-Discipline
ESSAYS Abiding Chance: Online Poker and the Software of Self- Discipline Natasha Dow Schüll A man sits before a large desktop monitor station, the double screen divided into twenty- four rectangles of equal size, each containing the green oval of a poker table with positions for nine players. The man is virtu- ally “seated” at all twenty- four tables, along with other players from around the world. He quickly navigates his mouse across the screen, settling for moments at a time on flashing windows where his input is needed to advance play at a given table. His rapid- fire esponsesr are enabled by boxed panels of colored numbers and letters that float above opponents’ names; the letters are acronyms for behavioral tendencies relevant to poker play, and the numbers are statistical scores identifying where each player falls in a range for those tendencies. Taken together, the letters and numbers supply the man with enough information to act strategically at a rate of hundreds of hands per hour. Postsession, the man opens his play- tracking database to make sure the software has successfully imported the few thousand hands he has just played. After quickly scrolling through to ensure that they are all there, he recalls some particularly challenging hands he would like to review and checks a number Thanks to Paul Rabinow and Limor Samimian- Darash, for prompting me to gather this material for a different article, and to Richard Fadok, Paul Gardner, Lauren Kapsalakis, and the students in my 2013 Self as Data graduate seminar at the Massachusetts Institute of Technology, for helping me to think through that material. -
Van Fleet Climbs to No
www.CardPlayer.com Vol. 34/No. 5 February 24, 2021 World Poker Tour Sells For $78 Million Q&A With Six-Time WSOP Circuit Winner Max Young Poker Strategy: The Wrong Time To Aggressively Play A Flush Draw JONATHAN ‘APESTYLES’ VAN FLEET CLIMBS TO NO. 3 ON ONLINE POKER’S ALL-TIME TOURNAMENT EARNINGS LIST PLAYER_35_5B_Cover.indd 1 2/4/21 9:43 AM PLAYER_05_GlobalPoker_DT.indd 2 2/2/21 10:24 AM PLAYER_05_GlobalPoker_DT.indd 3 2/2/21 10:24 AM Masthead - Card Player Vol. 34/No. 5 PUBLISHERS Barry Shulman | Jeff Shulman Editorial Corporate Office EDITORIAL DIRECTOR Julio Rodriguez 6940 O’Bannon Drive TOURNAMENT CONTENT MANAGER Erik Fast Las Vegas, Nevada 89117 ONLINE CONTENT MANAGER Steve Schult (702) 871-1720 Art [email protected] ART DIRECTOR Wendy McIntosh Subscriptions/Renewals 1-866-LVPOKER Website And Internet Services (1-866-587-6537) CHIEF TECHNOLOGY OFFICER Jaran Hardman PO Box 434 DATA COORDINATOR Morgan Young Congers, NY 10920-0434 Sales [email protected] ADVERTISING MANAGER Mary Hurbi Advertising Information NATIONAL SALES MANAGER Barbara Rogers [email protected] LAS VEGAS AND COLORADO SALES REPRESENTATIVE (702) 856-2206 Rich Korbin Distribution Information cardplayer Media LLC [email protected] CHAIRMAN AND CEO Barry Shulman PRESIDENT AND COO Jeff Shulman Results GENERAL COUNSEL Allyn Jaffrey Shulman [email protected] VP INTL. BUSINESS DEVELOPMENT Dominik Karelus CONTROLLER Mary Hurbi Schedules FACILITIES MANAGER Jody Ivener [email protected] Follow us www.facebook.com/cardplayer @CardPlayerMedia Card Player (ISSN 1089-2044) is published biweekly by Card Player Media LLC, 6940 O’Bannon Drive, Las Vegas, NV 89117. -
Early Round Bluffing in Poker Author(S): California Jack Cassidy Source: the American Mathematical Monthly, Vol
Early Round Bluffing in Poker Author(s): California Jack Cassidy Source: The American Mathematical Monthly, Vol. 122, No. 8 (October 2015), pp. 726-744 Published by: Mathematical Association of America Stable URL: http://www.jstor.org/stable/10.4169/amer.math.monthly.122.8.726 Accessed: 23-12-2015 19:20 UTC Your use of the JSTOR archive indicates your acceptance of the Terms & Conditions of Use, available at http://www.jstor.org/page/ info/about/policies/terms.jsp JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. For more information about JSTOR, please contact [email protected]. Mathematical Association of America is collaborating with JSTOR to digitize, preserve and extend access to The American Mathematical Monthly. http://www.jstor.org This content downloaded from 128.32.135.128 on Wed, 23 Dec 2015 19:20:53 UTC All use subject to JSTOR Terms and Conditions Early Round Bluffing in Poker California Jack Cassidy Abstract. Using a simplified form of the Von Neumann and Morgenstern poker calculations, the author explores the effect of hand volatility on bluffing strategy, and shows that one should never bluff in the first round of Texas Hold’Em. 1. INTRODUCTION. The phrase “the mathematics of bluffing” often brings a puzzled response from nonmathematicians. “Isn’t that an oxymoron? Bluffing is psy- chological,” they might say, or, “Bluffing doesn’t work in online poker. -
Abiding Chance: Online Poker and the Software of Self-Discipline
ESSAYS Abiding Chance: Online Poker and the Software of Self- Discipline Natasha Dow Schüll A man sits before a large desktop monitor station, the double screen divided into twenty- four rectangles of equal size, each containing the green oval of a poker table with positions for nine players. The man is virtu- ally “seated” at all twenty- four tables, along with other players from around the world. He quickly navigates his mouse across the screen, settling for moments at a time on flashing windows where his input is needed to advance play at a given table. His rapid- fire esponsesr are enabled by boxed panels of colored numbers and letters that float above opponents’ names; the letters are acronyms for behavioral tendencies relevant to poker play, and the numbers are statistical scores identifying where each player falls in a range for those tendencies. Taken together, the letters and numbers supply the man with enough information to act strategically at a rate of hundreds of hands per hour. Postsession, the man opens his play- tracking database to make sure the software has successfully imported the few thousand hands he has just played. After quickly scrolling through to ensure that they are all there, he recalls some particularly challenging hands he would like to review and checks a number Thanks to Paul Rabinow and Limor Samimian- Darash, for prompting me to gather this material for a different article, and to Richard Fadok, Paul Gardner, Lauren Kapsalakis, and the students in my 2013 Self as Data graduate seminar at the Massachusetts Institute of Technology, for helping me to think through that material. -
Article 3 Understanding Hand Strength After the Flop Pokerlist
Article 3 Understanding Hand Strength After The Flop Pokerlist.org For the most part, post flop play is determined by the strength of your hand and the relative hand strength of your opponent’s hand range. It sounds really complicated but it really isn’t. On the flop when the three community cards are dealt, you will have a better understanding of the strength of your hand and whether or not you should bet. If you have some type of made hand you have to decide if you likely have the best hand. It will almost become second nature to ask yourself how the flop could have changed the strength of your hand? Let’s take a look at the strength of hands to consider after the Flop. Monster hands don’t occur very often and include quads, boats, flushes, and straights. These hands are almost certainly the best hand if it goes to showdown and should be played like the nuts. You want to create big pots when you have monster hands. The second category is very strong hands, which include sets and two pair hands. Whenever you have these hands you likely have the best hand. Sure, you will sometimes lose with set over set, but if you are not playing sets and two pairs like the nuts, quite often you will not be extracting maximum value. Overpairs and top pair hands are the next group of strong hands. Depending on your opponents, with these hands you can usually expect to extract three streets of value when you are doing the betting. -
An Artificial Intelligence Agent for Texas Hold'em Poker
AN ARTIFICIAL INTELL IGENCE AGENT FOR TEXAS HOLD’EM PO KER PATRICK MCCURLEY – 0 62 4 91 7 90 2 An Artificial Intelligence Agent for Texas Hold’em Poker I declare that this document represents my own work except where otherwise stated. Signed …………………………………………………………………………. 08/05/ 2009 Patrick McCurley – 062491790 Introduction 3 TABLE OF CONTENTS 1. Introduction ................................................................................................................................................................ 7 1.1 Problem Description...................................................................................................................................... 7 1.2 Aims and Objectives....................................................................................................................................... 7 1.3 Dissertation Outline ....................................................................................................................................... 8 1.4 Ethics .................................................................................................................................................................... 8 2 Background................................................................................................................................................................10 2.1 Artificial Intelligence and Poker .............................................................................................................10 2.1.1 Problem Domain Realization .........................................................................................................10 -
Kill Everyone
Kill Everyone Advanced Strategies for No-Limit Hold ’Em Poker Tournaments and Sit-n-Go’s Lee Nelson Tysen Streib and Steven Heston Foreword by Joe Hachem Huntington Press Las Vegas, Nevada Contents Foreword.................................................................................. ix Author’s.Note.......................................................................... xi Introduction..............................................................................1 How.This.Book.Came.About...................................................5 Part One—Early-Stage Play . 1. New.School.Versus.Old.School.............................................9 . 2. Specific.Guidelines.for.Accumulating.Chips.......................53 Part Two—Endgame Strategy Introduction.........................................................................69 . 3. Basic.Endgame.Concepts....................................................71 . 4. Equilibrium.Plays................................................................89 . 5. Kill.Phil:.The.Next.Generation..........................................105 . 6. Prize.Pools.and.Equities....................................................115 . 7. Specific.Strategies.for.Different.Tournament.Types.........149 . 8. Short-Handed.and.Heads-Up.Play...................................179 . 9. Detailed.Analysis.of.a.Professional.SNG..........................205 Part Three—Other Topics .10. Adjustments.to.Recent.Changes.in.No-Limit Hold.’Em.Tournaments....................................................231 .11. Tournament.Luck..............................................................241 -
Building a Poker Playing Agent Based on Game Logs Using Supervised Learning
FACULDADE DE ENGENHARIA DA UNIVERSIDADE DO PORTO Building a Poker Playing Agent based on Game Logs using Supervised Learning Luís Filipe Guimarães Teófilo Mestrado Integrado em Engenharia Informática e Computação Orientador: Professor Doutor Luís Paulo Reis 26 de Julho de 2010 Building a Poker Playing Agent based on Game Logs using Supervised Learning Luís Filipe Guimarães Teófilo Mestrado Integrado em Engenharia Informática e Computação Aprovado em provas públicas pelo Júri: Presidente: Professor Doutor António Augusto de Sousa Vogal Externo: Professor Doutor José Torres Orientador: Professor Doutor Luís Paulo Reis ____________________________________________________ 26 de Julho de 2010 iv Resumo O desenvolvimento de agentes artificiais que jogam jogos de estratégia provou ser um domínio relevante de investigação, sendo que investigadores importantes na área das ciências de computadores dedicaram o seu tempo a estudar jogos como o Xadrez e as Damas, obtendo resultados notáveis onde o jogador artificial venceu os melhores jogadores humanos. No entanto, os jogos estocásticos com informação incompleta trazem novos desafios. Neste tipo de jogos, o agente tem de lidar com problemas como a gestão de risco ou o tratamento de informação não fiável, o que torna essencial modelar adversários, para conseguir obter bons resultados. Nos últimos anos, o Poker tornou-se um fenómeno de massas, sendo que a sua popularidade continua a aumentar. Na Web, o número de jogadores aumentou bastante, assim como o número de casinos online, tornando o Poker numa indústria bastante rentável. Além disso, devido à sua natureza estocástica de informação imperfeita, o Poker provou ser um problema desafiante para a inteligência artificial. Várias abordagens foram seguidas para criar um jogador artificial perfeito, sendo que já foram feitos progressos nesse sentido, como o melhoramento das técnicas de modelação de oponentes. -
Optimal Strategy Hand-Rank Table for Jacks Or Better, Double Bonus, and Joker Wild Video Poker
Optimal Strategy Hand-rank Table for Jacks or Better, Double Bonus, and Joker Wild Video Poker By John Jungtae Kim A Thesis Submitted to the School of Graduate Studies in Partial Fulfilment of the Requirements for the Degree Master of Science McMaster University c Copyright by John Jungtae Kim, January 2012 MASTER OF SCIENCE (2012) McMaster University (Statistics) Hamilton, Ontario TITLE: The Optimal Strategy Hand-rank Table for Jacks or Better, Double Bonus, and Joker Wild Video Poker AUTHOR: John Jungtae Kim (McMaster University, Canada) SUPERVISOR: Dr. Fred M. Hoppe NUMBER OF PAGES: viii, 76 i Abstract Video poker is a casino game based on five-card draw poker played on a computerized console. Video poker allows players an opportunity for some control of the random events that determine whether they win or lose. This means that making the right play can increase a player's return in the long run. For that reason, optimal strategy hand-rank tables for various types of video poker games have been recently published and established to help players improve their return (Ethier, 2010). Ethier posed a number of open problems in his recent book, The Doctrine of Chances: Probabilitistic Aspects of Gambling among which were some in video poker. In this thesis we consider the most popular video poker games: Jacks or Better, Double Bonus, and Joker Wild. Ethier produced an optimal strategy hand-rank table for Jacks or Better. We expand on his method to produce optimal hand-rank tables for Double Bonus,and Joker Wild. The method involves enumerating all possible discards, computing the expected returns, and then finding a way to rank them according to optimal discard based on the payoffs. -
Building a Champion Level Computer Poker Player
University of Alberta Library Release Form Name of Author: Michael Bradley Johanson Title of Thesis: Robust Strategies and Counter-Strategies: Building a Champion Level Computer Poker Player Degree: Master of Science Year this Degree Granted: 2007 Permission is hereby granted to the University of Alberta Library to reproduce single copies of this thesis and to lend or sell such copies for private, scholarly or scientific research purposes only. The author reserves all other publication and other rights in association with the copyright in the thesis, and except as herein before provided, neither the thesis nor any substantial portion thereof may be printed or otherwise reproduced in any material form whatever without the author’s prior written permission. Michael Bradley Johanson Date: Too much chaos, nothing gets finished. Too much order, nothing gets started. — Hexar’s Corollary University of Alberta ROBUST STRATEGIES AND COUNTER-STRATEGIES: BUILDING A CHAMPION LEVEL COMPUTER POKER PLAYER by Michael Bradley Johanson A thesis submitted to the Faculty of Graduate Studies and Research in partial fulfillment of the requirements for the degree of Master of Science. Department of Computing Science Edmonton, Alberta Fall 2007 University of Alberta Faculty of Graduate Studies and Research The undersigned certify that they have read, and recommend to the Faculty of Graduate Studies and Research for acceptance, a thesis entitled Robust Strategies and Counter-Strategies: Building a Champion Level Computer Poker Player submitted by Michael Bradley Johanson in partial fulfillment of the requirements for the degree of Master of Science. Michael Bowling Supervisor Duane Szafron Michael Carbonaro External Examiner Date: To my family: my parents Brad and Sue Johanson, and my brother, Jeff Johanson.