Unsupervised Domain Adaptation with Dynamics-Aware Rewards in Reinforcement Learning

no code implementations • NeurIPS 2021 • Jinxin Liu, Hao Shen, Donglin Wang, Yachen Kang, Qiangxing Tian

Unsupervised reinforcement learning aims to acquire skills without prior goal representations, where an agent automatically explores an open-ended environment to represent goals and learn the goal-conditioned policy.

reinforcement-learning Reinforcement Learning (RL) +2

Learn Goal-Conditioned Policy with Intrinsic Motivation for Deep Reinforcement Learning

no code implementations • 11 Apr 2021 • Jinxin Liu, Donglin Wang, Qiangxing Tian, Zhengyu Chen

It is of significance for an agent to learn a widely applicable and general-purpose policy that can achieve diverse goals including images and text descriptions.

reinforcement-learning Reinforcement Learning (RL)

Learning transitional skills with intrinsic motivation

no code implementations • 25 Sep 2019 • Qiangxing Tian, Jinxin Liu, Donglin Wang

By maximizing an information theoretic objective, a few recent methods empower the agent to explore the environment and learn useful skills without supervision.