Professional Poker Players' Modeling using Data-Mining

• Type: Article in International Conference Proceedings Book
• Date: 2016

Authors

Silva, N (Author) Other; reis, lp (Author) REIT

Conference proceedings International

Title: 11a Conferencia Ibérica de Sistemas y Tecnologías de Información

Indexing

ISI Web of Knowledge - 0 Citations

Scopus - 1 Citation

Other information

Authenticus ID: P-00K-S7G

DOI: 10.1109/cisti.2016.7521506

Abstract (EN): Poker has been gradually gaining the attention of the scientific community, mostly in researchers on Artificial Intelligence. The main reason is concerned with the fact that Poker provides great challenges to the research in the area. Unlike many other games, poker is a stochastic game of imperfect information, which creates a high amount of possibilities to every state of the game. In this work a different line of thought is followed by trying to create an agent capable of reproducing the way a professional Poker human player plays for all stages in a Texas Hold'em Poker game. For this purpose, a high level data model able to comprehend the maximum of information relevant to every state of the game was built, loaded with data from a database containing millions of plays made by a professional poker players, by using Talend Data Integration. To execute Data mining techniques Weka software package was used. The final results show that it is possible to create a virtual poker player that make very similar decisions of a professional poker player.

Language: Portuguese

Type (Professor's evaluation): Scientific

No. of pages: 6