Search Results for author: Mingxuan Jing

Found 4 papers, 1 papers with code

Adversarial Option-Aware Hierarchical Imitation Learning

1 code implementation10 Jun 2021 Mingxuan Jing, Wenbing Huang, Fuchun Sun, Xiaojian Ma, Tao Kong, Chuang Gan, Lei LI

In particular, we propose an Expectation-Maximization(EM)-style algorithm: an E-step that samples the options of expert conditioned on the current learned policy, and an M-step that updates the low- and high-level policies of agent simultaneously to minimize the newly proposed option-occupancy measurement between the expert and the agent.

Imitation Learning

Reinforcement Learning from Imperfect Demonstrations under Soft Expert Guidance

no code implementations16 Nov 2019 Mingxuan Jing, Xiaojian Ma, Wenbing Huang, Fuchun Sun, Chao Yang, Bin Fang, Huaping Liu

In this paper, we study Reinforcement Learning from Demonstrations (RLfD) that improves the exploration efficiency of Reinforcement Learning (RL) by providing expert demonstrations.

Learning and Inferring Movement with Deep Generative Model

no code implementations18 May 2018 Mingxuan Jing, Xiaojian Ma, Fuchun Sun, Huaping Liu

Learning and inference movement is a very challenging problem due to its high dimensionality and dependency to varied environments or tasks.

Motion Planning

Task Transfer by Preference-Based Cost Learning

no code implementations12 May 2018 Mingxuan Jing, Xiaojian Ma, Wenbing Huang, Fuchun Sun, Huaping Liu

The goal of task transfer in reinforcement learning is migrating the action policy of an agent to the target task from the source task.

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