We study a class of symmetric strategic experimentation games. Each of two players faces a (exponential) two-armed bandit problem, and must decide when to stop experimenting with the risky arm. The equilibrium amount of experimentation depends on the degree to which experimentation outcomes are...

We study a two-player, zero-sum, stochastic game with incomplete information on one side in which the players are allowed to play more and more frequently. The informed player observes the realization of a Markov chain on which the payoffs depend, while the non-informed player only observes his...

We revisit well-known models of learning in which a sequence of agents make a binary decision on the basis of a private signal and additional information. We introduce efficiency measures, aimed at capturing the speed of learning in such contexts. Whatever the distribution of private signals, we...