5 papers
Bandwidth-constrained Variational Message Encoding for Cooperative Multi-agent Reinforcement Learning
Wei Duan, Jie Lu, En Yu +1
Graph-based multi-agent reinforcement learning (MARL) enables coordinated behavior under partial observability by modeling agents as nodes and communication links as edges. While r…
Bayesian Ego-graph Inference for Networked Multi-Agent Reinforcement Learning
Wei Duan, Jie Lu, Junyu Xuan
In networked multi-agent reinforcement learning (Networked-MARL), decentralized agents must act under local observability and constrained communication over fixed physical graphs.…
Group-Aware Coordination Graph for Multi-Agent Reinforcement Learning
Wei Duan, Jie Lu, Junyu Xuan
Cooperative Multi-Agent Reinforcement Learning (MARL) necessitates seamless collaboration among agents, often represented by an underlying relation graph. Existing methods for lear…
Inferring Latent Temporal Sparse Coordination Graph for Multi-Agent Reinforcement Learning
Wei Duan, Jie Lu, Junyu Xuan
Effective agent coordination is crucial in cooperative Multi-Agent Reinforcement Learning (MARL). While agent cooperation can be represented by graph structures, prevailing graph l…
Functional Stochastic Gradient MCMC for Bayesian Neural Networks
Mengjing Wu, Junyu Xuan, Jie Lu
Classical parameter-space Bayesian inference for Bayesian neural networks (BNNs) suffers from several unresolved prior issues, such as knowledge encoding intractability and patholo…