MAVIPER: Learning Decision Tree Policies for Interpretable Multi-agent Reinforcement Learning. - Stephanie Milani; Zhicheng Zhang 003; Nicholay Topin; Zheyuan Ryan Shi; Charles A. Kamhoua; Evangelos E. Papalexakis; Fei Fang 001 (ECML/PKDD (4), 2022)

MESA: Cooperative Meta-Exploration in Multi-Agent Learning through Exploiting State-Action Space Structure. - Zhicheng Zhang 003; Yancheng Liang; Yi Wu 013; Fei Fang 001 (AAMAS, 2024)

Predicting and Presenting Task Difficulty for Crowdsourcing Food Rescue Platforms. - Zheyuan Ryan Shi; Jiayin Zhi; Siqi Zeng 001; Zhicheng Zhang 003; Ameesh Kapoor; Sean Hudson; Hong Shen 004; Fei Fang 001 (WWW, 2024)

M³HF: Multi-agent Reinforcement Learning from Multi-phase Human Feedback of Mixed Quality. - Ziyan Wang; Zhicheng Zhang 003; Fei Fang 001; Yali Du 001 (ICML, 2025)

M3HF: Multi-agent Reinforcement Learning from Multi-phase Human Feedback of Mixed Quality. - Ziyan Wang; Zhicheng Zhang 003; Fei Fang 001; Yali Du 001 (CoRR, 2025)

Making Teams and Influencing Agents: Efficiently Coordinating Decision Trees for Interpretable Multi-Agent Reinforcement Learning. - Rex Chen; Stephanie Milani; Zhicheng Zhang 003; Norman M. Sadeh; Fei Fang 001 (CoRR, 2025)

Learning Instruction-Following Policies through Open-Ended Instruction Relabeling with Large Language Models. - Zhicheng Zhang 003; Ziyan Wang; Yali Du 001; Fei Fang 001 (CoRR, 2025)

VAM: Verbalized Action Masking for Controllable Exploration in RL Post-Training - A Chess Case Study. - Zhicheng Zhang 003; Ziyan Wang; Yali Du 001; Fei Fang 001 (CoRR, 2026)