106,936 research outputs found

    Stochastic Inverse Reinforcement Learning

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    The goal of the inverse reinforcement learning (IRL) problem is to recover the reward functions from expert demonstrations. However, the IRL problem like any ill-posed inverse problem suffers the congenital defect that the policy may be optimal for many reward functions, and expert demonstrations may be optimal for many policies. In this work, we generalize the IRL problem to a well-posed expectation optimization problem stochastic inverse reinforcement learning (SIRL) to recover the probability distribution over reward functions. We adopt the Monte Carlo expectation-maximization (MCEM) method to estimate the parameter of the probability distribution as the first solution to the SIRL problem. The solution is succinct, robust, and transferable for a learning task and can generate alternative solutions to the IRL problem. Through our formulation, it is possible to observe the intrinsic property for the IRL problem from a global viewpoint, and our approach achieves a considerable performance on the objectworld.Comment: 8+2 pages, 5 figures, Under Revie

    Numerical analysis of parabolic p-Laplacian: Approximation of trajectories

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    The long time numerical approximation of the parabolic p-Laplacian problem with a time-independent forcing term and sufficiently smooth initial data is studied. Convergence and stability results which are uniform for t is an element of [0, infinity) are established in the L-2, W-1,W-p norms for the backward Euler and the Crank-Nicholson schemes with the finite element method (FEM). This result extends the existing uniform convergence results for exponentially contractive semigroups generated by some semilinear systems to nonexponentially contractive semigroups generated by some quasilinear systems

    Signatures of strong correlation effects in RIXS on Cuprates

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    Recently, spin excitations in doped cuprates are measured using the resonant inelastic X-ray scattering (RIXS). The paramagnon dispersions show the large hardening effect in the electron-doped systems and seemingly doping-independence in the hole-doped systems, with the energy scales comparable to that of the antiferromagnetic magnons. This anomalous hardening effect was partially explained by using the strong coupling t-J model but with a three-site term(Nature communications 5, 3314 (2014)). However we show that hardening effect is a signature of strong coupling physics even without including this extra term. By considering the t-t'-t"-J model and using the Slave-Boson (SB) mean field theory, we obtain, via the spin-spin susceptibility, the spin excitations in qualitative agreement with the experiments. These anomalies is mainly due to the doping-dependent bandwidth. We further discuss the interplay between particle-hole-like and paramagnon-like excitations in the RIXS measurements.Comment: 7 pages, 6 figure
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