Outline

Background What is Texas Hold'em? What are Bayesian Networks? What is BPP?

Aims Initial opponent model Adaptive opponent model Performance testing

Further Work Conclusion

Opponent Modeling in Bayesian Poker

Brendon Taylor (BSE)

Supervisors: Ann Nicholson Kevin Korb

http://www.allposters.com/-sp/Poker-Pups-II-Posters_i1611677_.htm

What is Texas Hold'em?

Poker Hands

From strongest to weakest

Poker Bayesian Network

What is BPP?

Bayesian Poker Program 1993: Initial version (Jitnah) 1999: First publication (Korb, Nicholson, Jitnah) 2000: Decision network (Carlton) 2003: Adapted to Texas Hold'em (Boulton)

Personality Types

Aggressive behaviour

More likely to bet/raise

Conservative behaviour

More likely to fold/check/call

AAAI 2006 Results - Bankroll

-1.1678

± 0.0427

0.1895

±0.0289

-0.4067

±0.0247

Teddy

(USA)

1.1678

±0.0427

-0.5271

±0.0197

-0.7227

±0.0161

Monash

(Monash U)

-0.1895

±0.0289

0.5271

±0.0197

-0.0514

±0.0171

Bluffbot

(Finland)

0.4067

±0.0247

0.7227

±0.0161

0.0514

±0.0171

Hyperborean

(U Alberta)

Teddy

(USA)

Monash

(Monash U)

Bluffbot

(Finland)

Hyperborean

(U Alberta)

Initial opponent modelAGGRESSIVECONSERVATIVE

New Network Structure

New node

Final opponent model

Generating different opponentsusing Betting Curves

Adapted from Carlton (2006)

Aggressive Conservative

Results - Opponent Type

Further Work

BPP's game play Improved bluffing strategy. Adding sand bagging. Avoiding predictable game play

Network structure Adding a OppTight node to the network. Adding a OppBluff node to the network. Adding a BppBehaviour node to the network.

Conclusion

BPP is an ongoing research project and still requires further work.

The improved opponent model has improved BPP's ability to adapt to an opponent.

This project has been challenging and taken me outside my comfort zone.

References

AAAI Computer Poker Competition (2006). http://www.cs.ualberta.ca/~pokert/2006/index.html

Aces High Casino Parties and Rentals San Antonio Texas (2007). http://www.aceshighcasinoparties.com

Carlton, J. (2000). Bayesian poker, Honours thesis, School of Computer Science and Software Engineering, Monash University.

Poker Pups II Prints by Jenny Newland at AllPosters.com (2007). http://www.allposters.com/-sp/Poker-Pups-II-Posters_i1611677_.htm

Taylor, B. (2007). Opponent Modeling in Bayesian Poker, Honours Thesis, School of Computer Science and Software Engineering, Monash University.

Aggressive opponent model

Conservative opponent model

Lessons Learnt

Honours is more challenging than under-graduate units.

Artificial Intelligence and decision making. Machine learning and structures. How to effectively research a topic. What to expect if I was to undertake further

post-graduate studies.