4 papers
SACHI: Structured Agent Coordination via Holistic Information Integration in Multi-Agent Reinforcement Learning
Nikunj Gupta, James Zachary Hare, Jesse Milzman +2
Cooperative multi-agent reinforcement learning agents that act on partial local observations face a fundamental information bottleneck: the knowledge needed to select jointly optim…
Action-Graph Policies: Learning Action Co-dependencies in Multi-Agent Reinforcement Learning
Nikunj Gupta, James Zachary Hare, Jesse Milzman +2
Coordinating actions is the most fundamental form of cooperation in multi-agent reinforcement learning (MARL). Successful decentralized decision-making often depends not only on go…
Deep Meta Coordination Graphs for Multi-agent Reinforcement Learning
Nikunj Gupta, James Zachary Hare, Jesse Milzman +2
This paper presents deep meta coordination graphs (DMCG) for learning cooperative policies in multi-agent reinforcement learning (MARL). Coordination graph formulations encode loca…
TIGER-MARL: Enhancing Multi-Agent Reinforcement Learning with Temporal Information through Graph-based Embeddings and Representations
Nikunj Gupta, Ludwika Twardecka, James Zachary Hare +3
In this paper, we propose capturing and utilizing \textit{Temporal Information through Graph-based Embeddings and Representations} or \textbf{TIGER} to enhance multi-agent reinforc…