Publications (40)
SA-MATD3:Self-attention-based multi-agent continuous control method in cooperative environments
Kai Liu, Yuyang Zhao, Gang Wang +1
Cooperative problems under continuous control have always been the focus of multi-agent reinforcement learning. Existing algorithms suffer from the problem of uneven learning degre…
A Knowledge-Informed Deep Learning Paradigm for Generalizable and Stability-Optimized Car-Following Models
Chengming Wang, Dongyao Jia, Wei Wang +3
Car-following models (CFMs) are fundamental to traffic flow analysis and autonomous driving. Although calibrated physics-based and trained data-driven CFMs can replicate human driv…
CURO: Curriculum Learning for Relative Overgeneralization
Lin Shi, Qiyuan Liu, Bei Peng
Relative overgeneralization (RO) is a pathology that can arise in cooperative multi-agent tasks when the optimal joint action's utility falls below that of a sub-optimal joint acti…
Heuristic Transformer: Belief Augmented In-Context Reinforcement Learning
Oliver Dippel, Alexei Lisitsa, Bei Peng
Transformers have demonstrated exceptional in-context learning (ICL) capabilities, enabling applications across natural language processing, computer vision, and sequential decisio…
DUAL: Dynamic Uncertainty-Aware Learning
Jiahao Qin, Bei Peng, Feng Liu +2
Deep learning models frequently encounter feature uncertainty in diverse learning scenarios, significantly impacting their performance and reliability. This challenge is particular…
RODE: Learning Roles to Decompose Multi-Agent Tasks
Tonghan Wang, Tarun Gupta, Anuj Mahajan +3
Role-based learning holds the promise of achieving scalable multi-agent learning by decomposing complex tasks using roles. However, it is largely unclear how to efficiently discove…