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Verifiable Reinforcement Learning via Policy Extraction

Osbert Bastani, Yewen Pu, Armando Solar-Lezama

Neural Information Processing Systems

Trajectoriestakenby , left : s 7! left, and right : s 7! rightareshownas dashededges, rededges, andgreenedges, respectively. Let ={ left : s 7! left, right : s 7! right}, andletg( )= Es d( )[g(s, )]bethe 0-1 loss.






A Proof and Derivations

Neural Information Processing Systems

However, the underlying clean model doesn't always exist for imperfect model Theorem A.1 (Necessary and Sufficient conditions for the existence of the underlying clean model.) . This theorem is a straightforward corollary of Bochner's I. (26) We can also expand the hessian of the log q We can then prove Theorem 2.3. All the experiments conducted in this paper are run on one single NVDIA GTX 3090.