Presentation on theme: "Outline Background What is Texas Hold'em? What are Bayesian Networks? What is BPP? Aims Initial opponent model Adaptive opponent model Performance."— Presentation transcript:
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
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.
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.