This paper extends the classic two-armed bandit problem to a many-agent setting in which I players each face the same experimentation problem. The main change from the single- agent problem is that an agent can now learn from the current experimentation of other agents. Information is therefore...

This paper extends the classic two-armed bandit problem to a many-agent setting in which N players each face the same experimentation problem. The difference with the single-agent problem is that agents can now learn from the experiments of others. Thus, experiementation produces a public good...

We study a dynamic-contracting problem involving risk sharing between two parties -- the Proposer and the Responder -- who invest in a risky asset until an exogenous but random termination time. In any time period they must invest all their wealth in the risky asset, but they can share the...

We study a dynamic-contracting problem involving risk sharing between two parties – the Proposer and the Responder – who invest in a risky asset until an exogenous but random termination time. In any time period they must invest all their wealth in the risky asset, but they can share the...

This paper extends the classic two-armed bandit problem to a many-agent setting in which N players each face the same experimentation problem. The main change from the single-agent problem is that an agent can now learn from the current experimentation of other agents. Information is therefore a...

This paper extends the classic two-armed bandit problem to a many-agent setting in which N players each face the same experimentation problem. The difference with the single-agent problem is that agents can now learn from the experiments of others. Thus, experiementation produces a public good...