A survey of progress on cooperative multi-agent reinforcement learning in open environment
Multi-agent Reinforcement Learning (MARL) has gained wide attention in recent years and
has made progress in various fields. Specifically, cooperative MARL focuses on training a …
has made progress in various fields. Specifically, cooperative MARL focuses on training a …
Efficient multi-agent communication via self-supervised information aggregation
Utilizing messages from teammates can improve coordination in cooperative Multi-agent
Reinforcement Learning (MARL). To obtain meaningful information for decision-making …
Reinforcement Learning (MARL). To obtain meaningful information for decision-making …
Learning multi-agent communication from graph modeling perspective
In numerous artificial intelligence applications, the collaborative efforts of multiple intelligent
agents are imperative for the successful attainment of target objectives. To enhance …
agents are imperative for the successful attainment of target objectives. To enhance …
Communication-robust multi-agent learning by adaptable auxiliary multi-agent adversary generation
Communication can promote coordination in cooperative Multi-Agent Reinforcement
Learning (MARL). Nowadays, existing works mainly focus on improving the communication …
Learning (MARL). Nowadays, existing works mainly focus on improving the communication …
Multi-agent cooperative strategy with explicit teammate modeling and targeted informative communication
Abstract The mainstream Multi-Agent Reinforcement Learning (MARL) methods introduce
the teammate modeling or the communication mechanism into Centralized Training …
the teammate modeling or the communication mechanism into Centralized Training …
T2MAC: Targeted and Trusted Multi-Agent Communication through Selective Engagement and Evidence-Driven Integration
Communication stands as a potent mechanism to harmonize the behaviors of multiple
agents. However, existing work primarily concentrates on broadcast communication, which …
agents. However, existing work primarily concentrates on broadcast communication, which …
Robust cooperative multi-agent reinforcement learning via multi-view message certification
Many multi-agent scenarios require message sharing among agents to promote
coordination, hastening the robustness of multi-agent communication when policies are …
coordination, hastening the robustness of multi-agent communication when policies are …
Communication Learning in Multi-Agent Systems from Graph Modeling Perspective
In numerous artificial intelligence applications, the collaborative efforts of multiple intelligent
agents are imperative for the successful attainment of target objectives. To enhance …
agents are imperative for the successful attainment of target objectives. To enhance …
Robust Multi-agent Communication via Multi-view Message Certification
Many multi-agent scenarios require message sharing among agents to promote
coordination, hastening the robustness of multi-agent communication when policies are …
coordination, hastening the robustness of multi-agent communication when policies are …
Revisiting Communication Efficiency in Multi-Agent Reinforcement Learning from the Dimensional Analysis Perspective
In this work, we introduce a novel perspective, ie, dimensional analysis, to address the
challenge of communication efficiency in Multi-Agent Reinforcement Learning (MARL). Our …
challenge of communication efficiency in Multi-Agent Reinforcement Learning (MARL). Our …