Deep Recurrent Deterministic Policy Gradient for Physical Control. - Lei Zhang; Shuai Han 005; Zhiruo Zhang; Lefan Li; Shuai Lü 001 (ICANN (2), 2020)

NROWAN-DQN: A Stable Noisy Network with Noise Reduction and Online Weight Adjustment for Exploration. - Shuai Han 005; Wenbo Zhou; Jing Liu; Shuai Lü 001 (CoRR, 2020)

Recruitment-imitation mechanism for evolutionary reinforcement learning. - Shuai Lü 001; Shuai Han 005; Wenbo Zhou; Junwei Zhang (Inf. Sci., 2021)

Regularly updated deterministic policy gradient algorithm. - Shuai Han 005; Wenbo Zhou; Shuai Lü 001; Jiayu Yu (Knowl. Based Syst., 2021)

NROWAN-DQN: A stable noisy network with noise reduction and online weight adjustment for exploration. - Shuai Han 005; Wenbo Zhou; Jiayi Lu; Jing Liu; Shuai Lü 001 (Expert Syst. Appl., 2022)

Sampling diversity driven exploration with state difference guidance. - Jiayi Lu; Shuai Han 005; Shuai Lü 001; Meng Kang; Junwei Zhang (Expert Syst. Appl., 2022)

Proximal policy optimization via enhanced exploration efficiency. - Junwei Zhang; Zhenghao Zhang; Shuai Han 005; Shuai Lü 001 (Inf. Sci., 2022)

Entropy regularization methods for parameter space exploration. - Shuai Han 005; Wenbo Zhou; Shuai Lü 001; Sheng Zhu; Xiaoyu Gong (Inf. Sci., 2023)

Guided deterministic policy optimization with gradient-free policy parameters information. - Chun Shen; Sheng Zhu; Shuai Han 005; Xiaoyu Gong; Shuai Lü 001 (Expert Syst. Appl., 2023)

Mixed experience sampling for off-policy reinforcement learning. - Jiayu Yu; Jingyao Li; Shuai Lü 001; Shuai Han 005 (Expert Syst. Appl., 2024)

Explorer-Actor-Critic: Better actors for deep reinforcement learning. - Junwei Zhang; Shuai Han 005; Xi Xiong; Sheng Zhu; Shuai Lü 001 (Inf. Sci., 2024)

VCSAP: Online reinforcement learning exploration method based on visitation count of state-action pairs. - Ruikai Zhou; Wenbo Zhu 003; Shuai Han 005; Meng Kang; Shuai Lü 001 (Neural Networks, 2025)