Efficient Prior-Free Mechanisms for No-Regret Agents

Understand

We study a repeated Principal Agent problem between a long lived Principal and Agent pair in a prior free setting.

• In our setting, the sequence of realized states of nature may be adversarially chosen, the Agent is non-myopic, and the Principal aims for a strong form of policy regret.
• Following Camara, Hartline, and Johnson, we model the Agent's long-run behavior with behavioral assumptions that relax the common prior assumption (for example, that the Agent has no swap regret).
• Within this framework, we revisit the mechanism proposed by Camara et al., which informally uses calibrated forecasts of the unknown states of nature in place of a common prior.