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arXiv · 2009.05518

Mechanisms for a No-Regret Agent: Beyond the Common Prior

Modibo Camara·Jason Hartline·Aleck Johnsen
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Abstract

A rich class of mechanism design problems can be understood as incomplete-information games between a principal who commits to a policy and an agent who responds, with payoffs determined by an unknown state of the world. Traditionally, these models require strong and often-impractical assumptions about beliefs (a common prior over the state). In this paper, we dispense with the common prior. Instead, we consider a repeated interaction where both the principal and the agent may learn over time from the state history. We reformulate mechanism design as a reinforcement learning problem and develop mechanisms that attain natural benchmarks without any assumptions on the state-generating process. Our results make use of novel behavioral assumptions for the agent -- centered around counterfactual internal regret -- that capture the spirit of rationality without relying on beliefs.

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Modibo Camara, Jason Hartline, Aleck Johnsen. 2020-09-11. Mechanisms for a No-Regret Agent: Beyond the Common Prior. https://arxiv.org/abs/2009.05518

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