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.
Weitere Kapitel dieses Buchs durch Wischen aufrufen
- Tutorial: Learning Topics in Game-Theoretic Decision Making
Michael L. Littman
- Springer Berlin Heidelberg