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Poki: The Poker Agent

Poki: The Poker Agent. Greg Priebe Zak Knudson. Overview. Texas Hold’em poker Architecture and Opponent Modeling of Poki Improvements from past Poki Betting strategies w/ analysis of hand strengths, weighting, and probabilities. Texas Hold’em. Each player gets 2 “hole” cards

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Poki: The Poker Agent

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  1. Poki: The Poker Agent Greg Priebe Zak Knudson

  2. Overview • Texas Hold’em poker • Architecture and Opponent Modeling of Poki • Improvements from past Poki • Betting strategies w/ analysis of hand strengths, weighting, and probabilities.

  3. Texas Hold’em • Each player gets 2 “hole” cards • Community cards: • 3 “flop” cards • 1 “turn” card • 1 “river” card • Rounds of betting after each set of cards

  4. Poki Program Architecture

  5. Opponent Modeling • Weight table • No modeling • Generic opponent modeling • Specific opponent modeling

  6. The Old Way • Specific opponent modeling • Betting frequency table • Keeps track of actions taken in different contexts • Predicts median hand strength • Left out many relevant details

  7. New and Improved • Specific opponent modeling • Detailed • Dynamic learning/adaptation • Prelim. Neural net study

  8. Poki’s Neural Net

  9. Some Results • Training Data • Results from 80-90 percent • Confusion matrix • Error prone?

  10. In Field Predictions #holdem1: 24% increase

  11. In Field Performance

  12. Small Bets Won • Pro: .05 - .10 • Old opponent modeling: .09 • New opponent modeling: .22

  13. Betting Strategy • Pre-flop and Post-flop strategies are significantly different. • Pre: little information available to influence the betting decision. • Post: uses opponent models, private hand, and game context to generate an action.

  14. Pre-flop Betting Strategy * - pocket pair hand (two cards of the same rank) s - suited hand o - offsuit hand

  15. Post-flop: Basic Betting Strategy • Compute Poki’s effective hand strength (EHS). • Using the game context, betting rules, and formulas to translate the EHS into a probability triple { Pr(fold), Pr(call), Pr(raise) }. • Generate a random number and use it to choose an action from the probability distribution.

  16. Hand Strength • Probability that a given hand is better than that of an active opponent.

  17. Hand Potential • With 2 cards yet to be revealed, we want to know the impact. • Positive potential (Ppot) – chance hand improves to win. • Negative potential (Npot) – chance hand ends up losing. • Calculated by enumerating over all possible hole cards, and over all possible board cards. • This is an expensive process.

  18. Hand potential example

  19. Effective Hand Strength • Combines hand strength and potential to give Poki’s own relative strength against an opponent. • Pr(win) = pr(ahead) * pr(opp doesn’t improve) + Pr(behind) * pr(we improve) = HS * (1 – Npot) + (1 – HS) * Ppot

  20. Weighting the Enumerations • Probability of hands played to a particular point will vary. • To account for this, Poki maintains a weight table for each opponent.

  21. Conclusions • Need opponent modeling • Complex system • Betting strategies and determining hand strength • Reweight helps to determine opponents likely action

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