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Yu-Ting Huang

2 accepted papers

2021

Robust Inverse Reinforcement Learning under Transition Dynamics Mismatch

NeurIPS 2021poster

We study the inverse reinforcement learning (IRL) problem under a transition dynamics mismatch between the expert and the learner. Specifically, we consider the Maximum Causal Entropy (MCE) IRL learner model and provide a tight upper bound on the learner's performance degradation based on the $\ell_…

2020

Robust Reinforcement Learning via Adversarial training with Langevin Dynamics

NeurIPS 2020poster

We introduce a \emph{sampling} perspective to tackle the challenging task of training robust Reinforcement Learning (RL) agents. Leveraging the powerful Stochastic Gradient Langevin Dynamics, we present a novel, scalable two-player RL algorithm, which is a sampling variant of the two-player policy g…

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