54 citations · 59 across the 9 of their papers we have counts for
10 papers
Conditional Diffusion Model for Multi-Agent Dynamic Task Decomposition
Yanda Zhu, Yuanyang Zhu, Daoyi Dong +2
Task decomposition has shown promise in complex cooperative multi-agent reinforcement learning (MARL) tasks, which enables efficient hierarchical learning for long-horizon tasks in…
High-order Interactions Modeling for Interpretable Multi-Agent Q-Learning
Qinyu Xu, Yuanyang Zhu, Xuefei Wu +1
The ability to model interactions among agents is crucial for effective coordination and understanding their cooperation mechanisms in multi-agent reinforcement learning (MARL). Ho…
Concept Learning for Cooperative Multi-Agent Reinforcement Learning
Zhonghan Ge, Yuanyang Zhu, Chunlin Chen
Despite substantial progress in applying neural networks (NN) to multi-agent reinforcement learning (MARL) areas, they still largely suffer from a lack of transparency and interope…
Learning Individual Intrinsic Reward in Multi-Agent Reinforcement Learning via Incorporating Generalized Human Expertise
Xuefei Wu, Xiao Yin, Yuanyang Zhu +1
Efficient exploration in multi-agent reinforcement learning (MARL) is a challenging problem when receiving only a team reward, especially in environments with sparse rewards. A pow…
Discretizing Continuous Action Space with Unimodal Probability Distributions for On-Policy Reinforcement Learning
Yuanyang Zhu, Zhi Wang, Yuanheng Zhu +2
For on-policy reinforcement learning, discretizing action space for continuous control can easily express multiple modes and is straightforward to optimize. However, without consid…
BiERL: A Meta Evolutionary Reinforcement Learning Framework via Bilevel Optimization
Junyi Wang, Yuanyang Zhu, Zhi Wang +3
Evolutionary reinforcement learning (ERL) algorithms recently raise attention in tackling complex reinforcement learning (RL) problems due to high parallelism, while they are prone…