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...

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 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 prove the existence of the maxmin of zero-sum recursive games with one sided information.

We study a class of symmetric strategic experimentation games. Each of two players faces an (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 class of symmetric strategic experimentation games. Each of two players faces an (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 focus on two-player, two-armed bandit games. We analyze the joint effect on the informational spillovers between the players of the correlation between the risky arms, and the extent to which one's experimentation results are publicly disclosed. Our main results only depend on whethert...