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.
Notice that the eachchpsq is the difference of two binomial random variablesb1 „BinpN, 1 ´γ β,λ,N q andb 2 „BinpN, γ β,λ,N q
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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.