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arXiv · 2607.18300

On Incentivized Exploration beyond Bayesianism and Full-Information

Dimitar Chakarov·Lee Cohen·Nathan Srebro
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Abstract

We extend Incentive Compatible Exploration beyond the Bayesian full-information setting of Kremer et al. [2014]. We consider agents that may possess external information unknown to the principal. We show such settings require new notions of incentivized exploration, as well as going beyond a Bayesian perspective, and we introduce a definition where agents choose any reasonable (undominated) action. Furthermore, our framework provides for a more robust treatment of ties, and extends to settings where agents lack a single common prior and instead only know that reward distributions belong to a collection of potential priors.

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Dimitar Chakarov, Lee Cohen, Nathan Srebro. 2026-07-14. On Incentivized Exploration beyond Bayesianism and Full-Information. https://arxiv.org/abs/2607.18300

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