We address the problem of learning and implementation on the Internet. When agents play repeated games in distributed … environments like the Internet, they have very limited {\em a priori} information about the other players and the payoff matrix … the essential properties that constitute ``reasonable'' learning behavior in distributed environments. We then study the …

We address the problem of learning and implementation on the Internet. When agents play repeated games in distributed … environments like the Internet, they have very limited {\em a priori} information about the other players and the payoff matrix … the essential properties that constitute ``reasonable'' learning behavior in distributed environments. We then study the …

-post implementation may not be possible. We propose direct (Bayesian) mechanisms that are robust to certain forms of bounded rationality … conditions for supermodular implementation in unique equilibrium. …

We propose a framework in order to econometrically estimate case-based learning and apply it to empirical data from … twelve 2 × 2 mixed strategy equilibria experiments. Case-based learning allows agents to explicitly incorporate information …-based learning to other learning models (reinforcement learning and self-tuned experience weighted attraction learning) while using …

A learning rule is uncoupled if a player does not condition his strategy on the opponent's payoffs. It is radically …, radically uncoupled learning rules whose period-by-period behavior comes arbitrarily close to Nash equilibrium behavior in any …

equilibrium of the game does not organize the individual data, two individual learning models are studied: one following a … predictive value of such learning models is found to be poor. …