Title :
Poker learner: Players modeling through data-mining
Author :
Silva, Nuno ; Reis, Luis Paulo
Author_Institution :
Dept. de Sist. de Informacao, Univ. do Minho, Guimaraes, Portugal
Abstract :
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.
Keywords :
computer games; data mining; data models; learning (artificial intelligence); CRISP-DM; ETL; ROC curve; Talend; Weka; data mining techniques; data model; extract-transform-and-load tool; poker learner; poker player model; Adaptation models; Computational modeling; Data mining; Data models; Games; Load modeling; Transforms; CRISP-DM; Weka; data mining; games; machine learning; poker; talend;
Conference_Titel :
Information Systems and Technologies (CISTI), 2015 10th Iberian Conference on
Conference_Location :
Aveiro
DOI :
10.1109/CISTI.2015.7170624