This book examines a conceptual framework for studying strategic learning. Topics include interactive learning problem; reinforcement and regret; equilibrium; conditional no-regret learning; prediction, postdiction, and calibration; fictitious play and its variants; Bayesian learning; and...

Decentralized matching markets on the internet allow large numbers of agents to interact anonymously at virtually no cost. Very little information is available to market participants and trade takes place at many different prices simultaneously. We propose a decentralized, completely uncoupled...

A learning rule is uncoupled if a player does not condition his strategy on the opponent's payoffs. It is radically uncoupled if a player does not condition his strategy on the opponent's actions or payoffs. We demonstrate a family of simple, radically uncoupled learning rules whose...