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2003 | OriginalPaper | Chapter

Tutorial: Learning Topics in Game-Theoretic Decision Making

Author: Michael L. Littman

Published in: Learning Theory and Kernel Machines

Publisher: Springer Berlin Heidelberg

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The tutorial will cover some topics of recent interest in AI and economics concerning design making in a computational game-theory framework. It will highlight areas in which computational learning theory has played a role and could play a greater role in the future. Covered areas include recent representational and algorithmic advances, stochastic games and reinforcement learning, no regret algorithms, and the role of various equilibrium concepts.

Metadata
Title
Tutorial: Learning Topics in Game-Theoretic Decision Making
Author
Michael L. Littman
Copyright Year
2003
Publisher
Springer Berlin Heidelberg
DOI
https://doi.org/10.1007/978-3-540-45167-9_1

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