Advertisement
Published in:
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
Included in: Professional Book Archive
Activate our intelligent search to find suitable subject content or patents.
Select sections of text to find matching patents with Artificial Intelligence. powered by
Select sections of text to find additional relevant content using AI-assisted search. powered by
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.