Building a no limit Texas hold'em poker agent based on game logs using supervised learning

• Type: Article in International Conference Proceedings Book
• Date: 2011

Authors

Luís Filipe Teófilo (Author) FEUP; Luís Paulo Reis (Author) FEUP

Conference proceedings International

Title: AUTONOMOUS AND INTELLIGENT SYSTEMS

Pages: 73-82

8th International Conference on Image Analysis and Recognition (ICIAR) / 2nd International Conference on Autonomous and Intelligent Systems (AIS)

Burnaby, CANADA, JUN 22-24, 2011

Indexing

ISI Web of Knowledge - 4 Citations

Scopus - 9 Citations

INSPEC

Scientific classification

FOS: Engineering and technology > Electrical engineering, Electronic engineering, Information engineering

Other information

Authenticus ID: P-002-Y2X

DOI: 10.1007/978-3-642-21538-4_8

Abstract (EN): The development of competitive artificial Poker players is a challenge to Artificial Intelligence (AI) because the agent must deal with unreliable information and deception which make it essential to model the opponents to achieve good results. In this paper we propose the creation of an artificial Poker player through the analysis of past games between human players, with money involved. To accomplish this goal, we defined a classification problem that associates a given game state with the action that was performed by the player. To validate and test the defined player model, an agent that follows the learned tactic was created. The agent approximately follows the tactics from the human players, thus validating this model. However, this approach alone is insufficient to create a competitive agent, as generated strategies are static, meaning that they can't adapt to different situations. To solve this problem, we created an agent that uses a strategy that combines several tactics from different players. By using the combined strategy, the agentgreatly improved its performance against adversaries capable of modeling opponents.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 10