16 papers
Finding Kissing Numbers with Game-theoretic Reinforcement Learning
Chengdong Ma, Théo Tao Zhaowei, Pengyu Li +7
Since Isaac Newton first studied the Kissing Number Problem in 1694, determining the maximal number of non-overlapping spheres around a central sphere has remained a defining chall…
Vulnerable Agent Identification in Large-Scale Multi-Agent Reinforcement Learning
Simin Li, Zihao Mao, Zheng Yuwei +12
Partial agent failure becomes inevitable when systems scale up, making it crucial to identify the subset of agents whose failure causes worst-case system performance degradations.…
System Design for Maintaining Internal State Consistency in Long-Horizon Robotic Tabletop Games
Guangyu Zhao, Ceyao Zhang, Chengdong Ma +16
Long-horizon tabletop games pose a distinct systems challenge for robotics: small perceptual or execution errors can invalidate accumulated task state, propagate across decision-ma…
Accelerating Robotic Reinforcement Learning with Agent Guidance
Haojun Chen, Zili Zou, Chengdong Ma +4
Reinforcement Learning (RL) offers a powerful paradigm for autonomous robots to master generalist manipulation skills through trial-and-error. However, its real-world application i…
Fusion-PSRO: Nash Policy Fusion for Policy Space Response Oracles
Jiesong Lian, Yucong Huang, Chengdong Ma +4
For solving zero-sum games involving non-transitivity, a useful approach is to maintain a policy population to approximate the Nash Equilibrium (NE). Previous studies have shown th…
World Models Should Prioritize the Unification of Physical and Social Dynamics
Xiaoyuan Zhang, Chengdong Ma, Yizhe Huang +5
World models, which explicitly learn environmental dynamics to lay the foundation for planning, reasoning, and decision-making, are rapidly advancing in predicting both physical dy…