8 citations · 14 across the 2 of their papers we have counts for
3 papers
cs.AI2021★ 8 cited
Learning Symbolic Rules for Interpretable Deep Reinforcement Learning
Zhihao Ma, Yuzheng Zhuang, Paul Weng +4
Recent progress in deep reinforcement learning (DRL) can be largely attributed to the use of neural networks. However, this black-box approach fails to explain the learned policy i…
cs.LG2020
Towards Effective Context for Meta-Reinforcement Learning: an Approach based on Contrastive Learning
Haotian Fu, Hongyao Tang, Jianye Hao +4
Context, the embedding of previous collected trajectories, is a powerful construct for Meta-Reinforcement Learning (Meta-RL) algorithms. By conditioning on an effective context, Me…
cs.AI2019★ 6 cited
Neighborhood Cognition Consistent Multi-Agent Reinforcement Learning
Hangyu Mao, Wulong Liu, Jianye Hao +5
Social psychology and real experiences show that cognitive consistency plays an important role to keep human society in order: if people have a more consistent cognition about thei…