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

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2011

Autores

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

Ata de Conferência Internacional

Título: AUTONOMOUS AND INTELLIGENT SYSTEMS

Páginas: 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

Indexação

ISI Web of Knowledge - 4 Citações

Scopus - 9 Citações

INSPEC

Classificação Científica

FOS: Ciências da engenharia e tecnologias > Engenharia electrotécnica, electrónica e informática

Outras Informações

ID Authenticus: 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.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 10