Improving Fictitious Play Reinforcement Learning with Expanding Models. - Rong-Jun Qin; Jing-Cheng Pang; Yang Yu 001 (CoRR, 2019)

Unified Policy Optimization for Continuous-action Reinforcement Learning in Non-stationary Tasks and Games. - Rong-Jun Qin; Fan-Ming Luo; Hong Qian; Yang Yu 001 (CoRR, 2022)

Adversarial Counterfactual Environment Model Learning. - Xiong-Hui Chen; Yang Yu 001; Zhengmao Zhu; Zhihua Yu; Zhenjun Chen; Chenghe Wang; Yinan Wu; Rong-Jun Qin; Hongqiu Wu; Ruijin Ding; Fangsheng Huang (NeurIPS, 2023)

Scaling Multi-Objective Security Games Provably via Space Discretization Based Evolutionary Search. - Yu-Peng Wu; Hong Qian; Rong-Jun Qin; Yi Chen; Aimin Zhou (CoRR, 2023)

Provable space discretization based evolutionary search for scalable multi-objective security games. - Hong Qian; Yu-Peng Wu; Rong-Jun Qin; Xin An; Yi Chen; Aimin Zhou (Swarm Evol. Comput., 2025)

Efficient Multi-Agent Cooperation Learning through Teammate Lookahead. - Feng Chen 042; Xinwei Chen; Rong-Jun Qin; Cong Guan; Lei Yuan 005; Zongzhang Zhang; Yang Yu 001 (Trans. Mach. Learn. Res., 2025)

NeoRL-2: Near Real-World Benchmarks for Offline Reinforcement Learning with Extended Realistic Scenarios. - Songyi Gao; Zuolin Tu; Rong-Jun Qin; Yi-Hao Sun; Xiong-Hui Chen; Yang Yu 001 (CoRR, 2025)