PSPL maintains posteriors over reward models and dynamics to deliver the first Bayesian simple regret guarantees for PbRL and outperforms baselines on simulation and image generation tasks.
xp1´xq.fis a concave function. We have for anyiP t0,1u, Prpπpiq k ‰π ‹q “E
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Best Policy Learning from Trajectory Preference Feedback
PSPL maintains posteriors over reward models and dynamics to deliver the first Bayesian simple regret guarantees for PbRL and outperforms baselines on simulation and image generation tasks.