no code implementations • 7 Feb 2024 • GuoJian Wang, Faguo Wu, Xiao Zhang, Jianxiang Liu
However, existing methods often require these experiences to be successful and may overly exploit them, which can cause the agent to adopt suboptimal behaviors.
no code implementations • 4 Jan 2024 • GuoJian Wang, Faguo Wu, Xiao Zhang
The proposed algorithm undergoes evaluation across extensive discrete and continuous control tasks with sparse and misleading rewards.
no code implementations • 30 Dec 2023 • GuoJian Wang, Faguo Wu, Xiao Zhang, Tianyuan Chen, Zhiming Zheng
The sparsity of reward feedback remains a challenging problem in online deep reinforcement learning (DRL).
1 code implementation • 27 Dec 2023 • GuoJian Wang, Faguo Wu, Xiao Zhang, Ning Guo, Zhiming Zheng
Deep reinforcement learning (DRL) faces significant challenges in addressing the hard-exploration problems in tasks with sparse or deceptive rewards and large state spaces.