A Logarithmic Barrier Method For Proximal Policy Optimization. - Cheng Zeng; Hongming Zhang 003 (CoRR, 2018)

RevCuT Tree Search Method in Complex Single-player Game with Continuous Search Space. - Hongming Zhang 003; Fangjuan Cheng; Bo Xu 002; Feng Chen; Jiachen Liu; Wei Wu (IJCNN, 2019)

Iterative Update and Unified Representation for Multi-Agent Reinforcement Learning. - Jiancheng Long; Hongming Zhang 003; Tianyang Yu; Bo Xu 002 (CoRR, 2019)

RLzoo: A Comprehensive and Adaptive Reinforcement Learning Library. - Zihan Ding; Tianyang Yu; Yanhua Huang; Hongming Zhang 003; Luo Mai; Hao Dong 003 (CoRR, 2020)

Efficient Reinforcement Learning Development with RLzoo. - Zihan Ding; Tianyang Yu; Hongming Zhang 003; Yanhua Huang; Guo Li; Quancheng Guo; Luo Mai; Hao Dong 003 (ACM Multimedia, 2021)

A Simple Unified Framework for Anomaly Detection in Deep Reinforcement Learning. - Hongming Zhang 003; Ke Sun 013; Bo Xu 002; Linglong Kong; Martin Müller 003 (CoRR, 2021)

Build generally reusable agent-environment interaction models. - Jun Jin 001; Hongming Zhang 003; Jun Luo 009 (CoRR, 2022)

PiCor: Multi-Task Deep Reinforcement Learning with Policy Correction. - Fengshuo Bai; Hongming Zhang 003; Tianyang Tao; Zhiheng Wu; Yanna Wang; Bo Xu 002 (AAAI, 2023)

Replay Memory as An Empirical MDP: Combining Conservative Estimation with Experience Replay. - Hongming Zhang 003; Chenjun Xiao; Han Wang; Jun Jin 001; Bo Xu 002; Martin Müller 003 (ICLR, 2023)

Monte Carlo Tree Search in the Presence of Transition Uncertainty. - Farnaz Kohankhaki; Kiarash Aghakasiri; Hongming Zhang 003; Ting-Han Wei; Chao Gao; Martin Müller 003 (AAAI, 2024)

Exploiting the Replay Memory Before Exploring the Environment: Enhancing Reinforcement Learning Through Empirical MDP Iteration. - Hongming Zhang 003; Chenjun Xiao; Chao Gao; Han Wang; Bo Xu 002; Martin Müller 003 (NeurIPS, 2024)

Efficient Preference-based Reinforcement Learning via Aligned Experience Estimation. - Fengshuo Bai; Rui Zhao 001; Hongming Zhang 003; Sijia Cui; Ying Wen 001; Yaodong Yang 001; Bo Xu 002; Lei Han (CoRR, 2024)

A Distance-based Anomaly Detection Framework for Deep Reinforcement Learning. - Hongming Zhang 003; Ke Sun 013; Bo Xu 002; Linglong Kong; Martin Müller 003 (Trans. Mach. Learn. Res., 2024)

β-DQN: Improving Deep Q-Learning By Evolving the Behavior. - Hongming Zhang 003; Fengshuo Bai; Chenjun Xiao; Chao Gao; Bo Xu 002; Martin Müller 003 (AAMAS, 2025)

Latent Landmark Graph for Efficient Exploration-exploitation Balance in Hierarchical Reinforcement Learning. - Qingyang Zhang; Hongming Zhang 003; Dengpeng Xing; Bo Xu 002 (Int. J. Autom. Comput., 2025)

Self-Guided Function Calling in Large Language Models via Stepwise Experience Recall. - Sijia Cui; Aiyao He; Shuai Xu; Hongming Zhang 003; Yanna Wang; Qingyang Zhang; Yajing Wang; Bo Xu 002 (CoRR, 2025)