We present the results of an experiment on learning in a continuous-time low-information setting. For a Cournot oligopoly with differentiated products, a dominance solvable game, we find little evidence of convergence to the Nash equilibrium. In an asynchronous setting, play tends toward the...

We present the results of an experiment on learning in a continuous-time low-information setting. For a Cournot oligopoly with differentiated products, a dominance solvable game, we find little evidence of convergence to the Nash equilibrium. In an asynchronous setting, play tends toward the...

We present the results of an experiment on learning in a continuous-time low-information setting. For a dominance solvable version of a Cournot oligopoly with differentiated products, we find little evidence of convergence to the Nash equilibrium. In an asynchronous setting, characterized by...

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, and the play can be highly asynchronous....

This paper describes the results of simulation experiments performed on a suite of learning algorithms. We focus on games in {\em network contexts}. These are contexts in which (1) agents have very limited information about the game; users do not know their own (or any other agent's) payoff...