Poker Learner: Players Modeling Through Data-Mining

• Type: Article in International Conference Proceedings Book
• Date: 2015

Authors

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

Conference proceedings International

Title: 2015 10TH IBERIAN CONFERENCE ON INFORMATION SYSTEMS AND TECHNOLOGIES (CISTI)

10th Iberian Conference on Information Systems and Technologies (CISTI)

Univ Aveiro, Sch Technol & Agueda Management, Agueda, PORTUGAL, JUN 17-20, 2015

Indexing

ISI Web of Knowledge - 0 Citations

Scopus - 3 Citations

Other information

Authenticus ID: P-00G-PVY

DOI: 10.1109/cisti.2015.7170624

Abstract (EN): In recent years the game of poker has created a high interest on researchers from the artificial intelligence area. Unlike board games, poker is an incomplete information game becoming a very complex game for a virtual agent. The main objective of this work is to create a data model enabling to apply data mining techniques to obtain a poker player model (pre-flop stage). To do that we used a database from a professional poker player where the data is stored in text files. The work used CRISP-DM, performing its stages. As ETL (Extract, Transform and Load) tool Talend was used and for running the data mining techniques Weka was used. As a final result, a player model was achieved with a very good ROC curve. This result, enable us to conclude that the approach is adequate for creating complete poker player models.

Language: Portuguese

Type (Professor's evaluation): Scientific

No. of pages: 6