Texas Hold’em Playing Styles Team 4 Matt Darryl Alex.

Slides:



Advertisements
Similar presentations
Bet sizing – How much to bet and why? Strategy: SnG / Tournaments.
Advertisements

Advanced Strategies for Craps and Poker Billy J. Duke Joel A. Johnson.
On Von Neumann Poker with Community Cards Reto Spöhel Joint work with Nicla Bernasconi and Julian Lorenz TexPoint fonts used in EMF. Read the TexPoint.
Virtual Host: John Morales Revised: September 21, 2011 Project 4: Multi-media Lesson.
After the flop – an opponent raised before the flop Strategy: No-Limit.
After the flop – nobody raised before the flop Strategy: No-Limit.
Tuomas Sandholm, Andrew Gilpin Lossless Abstraction of Imperfect Information Games Presentation : B 趙峻甫 B 蔡旻光 B 駱家淮 B 李政緯.
Short Stack Strategy – How to play after the flop Strategy: No Limit.
Neural Networks for Opponent Modeling in Poker John Pym.
Dealer Comm Hand Player makes Ante bet and optional Bonus bet. Five cards are dealt to each player from the shuffler. Five cards are dealt from the shuffler.
Card Counting What is it, how does it work, and can I use it to pay for college? (and if it does work, do I even have to go to college?) Jeff O’Connell.
Final Specification KwangMonarchIkhanJamesGraham.
Mathematics and the Game of Poker
Rene Plowden Joseph Libby. Improving the profit margin by optimizing the win ratio through the use of various strategies and algorithmic computations.
Intelligence for Games and Puzzles1 Poker: Opponent Modelling Early AI work on poker used simplified.
Texas Hold’em Poker Simulation Project Monarch ^ James Ikhan Kwang Graham Devin Organized by M^JIK Game Developers Members Include:
Intro to Probability & Games
Jerad Hobgood.  24/7 Accessibility  Fast Games  No tipping  No travel  Find table in your price range  Play in more than one table at a time.
Poki: The Poker Agent Greg Priebe Zak Knudson. Overview Texas Hold’em poker Architecture and Opponent Modeling of Poki Improvements from past Poki Betting.
Introduction to the Big Stack Strategy (BSS) Strategy: No Limit.
Quark Card Game by Helio Takai (and dice game)
Texas Holdem Poker With Q-Learning. First Round (pre-flop) PlayerOpponent.
Overview Odds Pot Odds Outs Probability to Hit an Out
Stat 35b: Introduction to Probability with Applications to Poker Outline for the day: 1.Straight draws. 2.HW2 clarification. 3.Greenstein vs. Farha AA.
Brian Duddy.  Two players, X and Y, are playing a card game- goal is to find optimal strategy for X  X has red ace (A), black ace (A), and red two (2)
Sonny Thomas Macdonald SONNY THOMAS MACDONALD 2010 Internet Computing Bsc.
Brain Teasers. Answer 3 Quantitative Finance Society Gambling Strategies & Statistics.
Introduction for Rotarians
NearOptimalGamblingAdive Matt Morgis Peter Chapman Mitch McCann Temple University.
Poker Download A most popular card game or group of card games is called poker. Players compete against one another by betting on the values of each player's.
Learning to Play KardKuro Goals: Have Fun while Practicing Addition and Subtraction. Improve Social Learning Opportunities with Classmates. Become familiar.
Suppose someone bets (or raises) you, going all-in. What should your chances of winning be in order for you to correctly call? Let B = the amount bet to.
SARTRE: System Overview A Case-Based Agent for Two-Player Texas Hold'em Jonathan Rubin & Ian Watson University of Auckland Game AI Group
Quark Card Game by Helio Takai (and dice game)
The challenge of poker NDHU CSIE AI Lab 羅仲耘. 2004/11/04the challenge of poker2 Outline Introduction Texas Hold’em rules Poki’s architecture Betting Strategy.
Poker as a Testbed for Machine Intelligence Research By Darse Billings, Dennis Papp, Jonathan Schaeffer, Duane Szafron Presented By:- Debraj Manna Gada.
Outline for the day: 1.Discuss handout / get new handout. 2.Teams 3.Example projects 4.Expected value 5.Pot odds calculations 6.Hansen / Negreanu 7.P(4.
Yikan Chen Weikeng Qin 1.
Neural Network Implementation of Poker AI
Stat 35b: Introduction to Probability with Applications to Poker Outline for the day: 1.Addiction 2.Syllabus, etc. 3. Wasicka/Gold/Binger Example 4.Meaning.
Stat 35b: Introduction to Probability with Applications to Poker Outline for the day: 1.Deal-making and expected value 2.Odds ratios, revisited 3.Variance.
The Poker Game in Jadex by Group 1 Mohammed Musavi (Ashkan) Xavi Dolcet Enric Tejedor.
WOULD YOU PLAY THIS GAME? Roll a dice, and win $1000 dollars if you roll a 6.
Short stack strategy: Draws in a free play situation Strategy: No Limit.
Finding Probability Using Tree Diagrams and Outcome Tables
All In To put all the rest of your money into the pot.
Introduction to Poker Originally created by Albert Wu,
Penn Poker Fall Strategy Session Series
Stat 35b: Introduction to Probability with Applications to Poker Outline for the day: 1.Odds ratios revisited. 2.Gold/Hellmuth. 3.Deal making. 4.Variance.
Artificial Neural Networks And Texas Hold’em ECE 539 Final Project December 19, 2003 Andy Schultz.
By: John Cook 11/06/2009 PTTE John Cook 3/4/2016.
The Mathematics of Poker– Implied Pot Odds Strategy: No-Limit.
Stat 35b: Introduction to Probability with Applications to Poker Outline for the day: 1. Combos, permutations, and A  vs 2  after first ace 2.Conditional.
Stat 35b: Introduction to Probability with Applications to Poker Outline for the day: 1.Expected value. 2.Heads up with AA. 3.Heads up with Gus vs.
JokerStars: Online Card Playing William Sanville Milestone 5.
Texas Holdem A Poker Variant vs. Flop TurnRiver. How to Play Everyone is dealt 2 cards face down (Hole Cards) 5 Community Cards Best 5-Card Hand Wins.
Stat 35b: Introduction to Probability with Applications to Poker
Game Theory Just last week:
Stat 35b: Introduction to Probability with Applications to Poker
Stat 35b: Introduction to Probability with Applications to Poker
Stat 35b: Introduction to Probability with Applications to Poker
THE TEXAS HOLD’EM.
Strategies for Poker AI player
Probability of casino games
Stat 35b: Introduction to Probability with Applications to Poker
Stat 35b: Introduction to Probability with Applications to Poker
Stat 35b: Introduction to Probability with Applications to Poker
Stat 35b: Introduction to Probability with Applications to Poker
Stat 35b: Introduction to Probability with Applications to Poker
HOW TO PLAY POKER.
Presentation transcript:

Texas Hold’em Playing Styles Team 4 Matt Darryl Alex

Goals  Have our different players feel unique in the way they play the game  Have the Texas hold’em our players play look and feel like the real thing  Have our players adopt strategy to playing that mimic the professionals

Formal Statement of Problem  To find in Texas Hold'em, the play style such that given a finite amount of chips in the game, against any other play style, one play style will end with all chips in play.

How to Play Texas Hold’em  Players are dealt two cards to begin  Players can bet, check, or fold based on their hand  After everyone has finished there starting bets the dealer flips over on the the table three more cards called the flop  After the flop players again go around the table betting, calling, and folding  Once the round of betting is over the dealer flips one more card, and the round of betting starts again.  After the final card called the river is flipped over onto the table, the final round of betting begins.  After the final round of betting all remaining players flip there hands and the player with the best combination wins the pot.

Hand Strength

MoneyBags  Not afraid to bet large  Willing to play many starting hands regardless of strength  Aggressive play style  A naïve approach to poker with not much consideration to what the other players are doing

The Cheapskate  Will only play the best starting hands  A very patient playstyle playing only hands he thinks he will win with  When his hand is well will play big pots

Joe Schmoe  The test case, what we consider the average player  Will play more hands than CheapSkate but less than MoneyBags.  An average between the two extremes of MoneyBags and CheapSkate

Starting Hand Ranking

How it works  Each player will react differently to the same starting hand dealt with every player having a different threshold of quality of starting hand willing to play, and there hand rank and board state determining the amount of money to bet or to fold.  After finishing the starting hand and the first round of bets and folds, each player than use some statistical analysis to look at the amount of outs over the amount of cards left to draw, and the strength of the outs.  Outs we define as the card that can be drawn at any point to complete any one of the winning card combinations  Ex. If your hand consists of 6, 7 suited and the board consists of 5,8,K, your projected outs for a flush is 8/47 not considering other players hands.

Questions ● Question - How does the probability of the hands affect the bets the different players make? ● Answer – Each player has a defined starting bet value and that is multiplied against a combined probability of the hand given any amount of cards left to draw. ● Question- Under what circumstances would a player fold there hand? ● Answer – Using the same starting bet value defined for each player, a player will fold when their amount they would bet is smaller by some margin then the current bet. ● Question – The players do not use the same probabilities for there starting hand that they use for post flop calculations. What is the metric for grading starting hands? ● Answer – Each two card starting hand has precalculated value ranging from 1 to 4, one being the best possible two card combo, 8 being the worst. ● Questions – Explain simply in a few adjectives each players style? ● Answer – MoneyBags -Naïve, large bets; CheapSkate – passive, patient; Joe Schmoe – a mix of both, right in the middle ● Questions – How would these players fair against real players? ● Answer – Would not do well, Texas Hold’em can be a very mental game where you are trying to guess the other players hand and with any computer controlled players they can become very predictable.