3rd International Symposium on
Imprecise Probabilities and Their Applications

ISIPTA '03

University of Lugano
Lugano, Switzerland
14-17 July 2003

ELECTRONIC PROCEEDINGS

Erik Quaeghebeur, Gert de Cooman

Game-Theoretic Learning Using the Imprecise Dirichlet Model

Abstract

We discuss two approaches for choosing a strategy in a two-player game. We suppose that the game is played a large number of rounds, which allows the players to use observations of past play to guide them in choosing a strategy. Central in these approaches is the way the opponent's next strategy is assessed; both a precise and an imprecise Dirichlet model are used. The observations of the opponent's past strategies can then be used to update the model and obtain new assessments. To some extent, the imprecise probability approach allows us to avoid making arbitrary initial assessments. To be able to choose a strategy, the assessment of the opponent's strategy is combined with rules for selecting an optimal response to it: a so-called best response or a maximin strategy. Together with the updating procedure, this allows us to choose strategies for all the rounds of the game. The resulting playing sequence can then be analysed to investigate if the strategy choices can converge to equilibria.

Keywords. game theory, fictitious play, equilibria, imprecise Dirichlet model, learning

Paper Download

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Authors addresses:

Erik Quaeghebeur
research group SYSTeMS
Technologiepark - Zwijnaarde 914
B-9052 Zwijnaarde

Gert de Cooman
Universiteit Gent
Onderzoeksgroep SYSTeMS
Technologiepark - Zwijnaarde 9
9052 Zwijnaarde
Belgium

E-mail addresses:

Erik Quaeghebeur Erik.Quaeghebeur@rug.ac.be
Gert de Cooman gert.decooman@rug.ac.be


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