Self-Supervised Exploration via Temporal Inconsistency in Reinforcement Learning

no code implementations • 24 Aug 2022 • Zijian Gao, Kele Xu, Yuanzhao Zhai, Dawei Feng, Bo Ding, XinJun Mao, Huaimin Wang

Our method involves training a self-supervised prediction model, saving snapshots of the model parameters, and using nuclear norm to evaluate the temporal inconsistency between the predictions of different snapshots as intrinsic rewards.

reinforcement-learning Reinforcement Learning (RL)

Dynamic Memory-based Curiosity: A Bootstrap Approach for Exploration

no code implementations • 24 Aug 2022 • Zijian Gao, Yiying Li, Kele Xu, Yuanzhao Zhai, Dawei Feng, Bo Ding, XinJun Mao, Huaimin Wang

The curiosity arouses if memorized information can not deal with the current state, and the information gap between dual learners can be formulated as the intrinsic reward for agents, and then such state information can be consolidated into the dynamic memory.

Reinforcement Learning (RL)