Communication Learning in Multi-Agent Systems from Graph Modeling Perspective
Fuente:
arXiv
Saved in:
| Main Authors: | Hu, Shengchao, Shen, Li, Zhang, Ya, Tao, Dacheng |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Learning Multi-Agent Communication from Graph Modeling Perspective
by: Hu, Shengchao, et al.
Published: (2024)
by: Hu, Shengchao, et al.
Published: (2024)
Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency
by: Zhang, Qixin, et al.
Published: (2025)
by: Zhang, Qixin, et al.
Published: (2025)
Effective Policy Learning for Multi-Agent Online Coordination Beyond Submodular Objectives
by: Zhang, Qixin, et al.
Published: (2025)
by: Zhang, Qixin, et al.
Published: (2025)
Cut the Crap: An Economical Communication Pipeline for LLM-based Multi-Agent Systems
by: Zhang, Guibin, et al.
Published: (2024)
by: Zhang, Guibin, et al.
Published: (2024)
Fully Independent Communication in Multi-Agent Reinforcement Learning
by: Pina, Rafael, et al.
Published: (2024)
by: Pina, Rafael, et al.
Published: (2024)
Graph Attention Inference of Network Topology in Multi-Agent Systems
by: Kolli, Akshay, et al.
Published: (2024)
by: Kolli, Akshay, et al.
Published: (2024)
OFA-MAS: One-for-All Multi-Agent System Topology Design based on Mixture-of-Experts Graph Generative Models
by: Li, Shiyuan, et al.
Published: (2026)
by: Li, Shiyuan, et al.
Published: (2026)
Cooperative Multi-Agent Graph Bandits: UCB Algorithm and Regret Analysis
by: Paschalidis, Phevos, et al.
Published: (2024)
by: Paschalidis, Phevos, et al.
Published: (2024)
A Survey of Multi-Agent Deep Reinforcement Learning with Communication
by: Zhu, Changxi, et al.
Published: (2022)
by: Zhu, Changxi, et al.
Published: (2022)
MasRouter: Learning to Route LLMs for Multi-Agent Systems
by: Yue, Yanwei, et al.
Published: (2025)
by: Yue, Yanwei, et al.
Published: (2025)
Context-aware Communication for Multi-agent Reinforcement Learning
by: Li, Xinran, et al.
Published: (2023)
by: Li, Xinran, et al.
Published: (2023)
Self-Confirming Transformer for Belief-Conditioned Adaptation in Offline Multi-Agent Reinforcement Learning
by: Li, Tao, et al.
Published: (2023)
by: Li, Tao, et al.
Published: (2023)
Revisiting Multi-Agent World Modeling from a Diffusion-Inspired Perspective
by: Zhang, Yang, et al.
Published: (2025)
by: Zhang, Yang, et al.
Published: (2025)
Robust Multi-agent Communication via Multi-view Message Certification
by: Yuan, Lei, et al.
Published: (2023)
by: Yuan, Lei, et al.
Published: (2023)
Multi-Agent Coordination via Multi-Level Communication
by: Ding, Ziluo, et al.
Published: (2022)
by: Ding, Ziluo, et al.
Published: (2022)
Stronger-MAS: Multi-Agent Reinforcement Learning for Collaborative LLMs
by: Zhao, Yujie, et al.
Published: (2025)
by: Zhao, Yujie, et al.
Published: (2025)
Inferring Latent Temporal Sparse Coordination Graph for Multi-Agent Reinforcement Learning
by: Duan, Wei, et al.
Published: (2024)
by: Duan, Wei, et al.
Published: (2024)
Graph-SND: Sparse Aggregation for Behavioral Diversity in Multi-Agent Reinforcement Learning
by: Ray, Shawn
Published: (2026)
by: Ray, Shawn
Published: (2026)
Approximate Global Convergence of Independent Learning in Multi-Agent Systems
by: Jin, Ruiyang, et al.
Published: (2024)
by: Jin, Ruiyang, et al.
Published: (2024)
Generalized Intention Modeling in Multi-Agent Reinforcement Learning
by: Odrowaz-Sypniewski, Mateusz, et al.
Published: (2026)
by: Odrowaz-Sypniewski, Mateusz, et al.
Published: (2026)
Learning to Communicate in Multi-Agent Reinforcement Learning for Autonomous Cyber Defence
by: Contractor, Faizan, et al.
Published: (2025)
by: Contractor, Faizan, et al.
Published: (2025)
Learning Graph Representation of Agent Diffusers
by: Djenouri, Youcef, et al.
Published: (2025)
by: Djenouri, Youcef, et al.
Published: (2025)
MACTAS: Self-Attention-Based Inter-Agent Communication in Multi-Agent Reinforcement Learning with Action-Value Function Decomposition
by: Wojtala, Maciej, et al.
Published: (2025)
by: Wojtala, Maciej, et al.
Published: (2025)
Continuous-Time Value Iteration for Multi-Agent Reinforcement Learning
by: Wang, Xuefeng, et al.
Published: (2025)
by: Wang, Xuefeng, et al.
Published: (2025)
Double Distillation Network for Multi-Agent Reinforcement Learning
by: Zhou, Yang, et al.
Published: (2025)
by: Zhou, Yang, et al.
Published: (2025)
CAMMARL: Conformal Action Modeling in Multi Agent Reinforcement Learning
by: Gupta, Nikunj, et al.
Published: (2023)
by: Gupta, Nikunj, et al.
Published: (2023)
Active Learning for Communication Structure Optimization in LLM-Based Multi-Agent Systems
by: Yang, Huchen, et al.
Published: (2026)
by: Yang, Huchen, et al.
Published: (2026)
A Survey of Multi-Agent Deep Reinforcement Learning with Graph Neural Network-Based Communication
by: Cuzin-Rambaud, Valentin, et al.
Published: (2026)
by: Cuzin-Rambaud, Valentin, et al.
Published: (2026)
UAV-Assisted Multi-Task Federated Learning with Task Knowledge Sharing
by: Yang, Yubo, et al.
Published: (2025)
by: Yang, Yubo, et al.
Published: (2025)
GoAgent: Group-of-Agents Communication Topology Generation for LLM-based Multi-Agent Systems
by: Chen, Hongjiang, et al.
Published: (2026)
by: Chen, Hongjiang, et al.
Published: (2026)
Transformer World Model for Sample Efficient Multi-Agent Reinforcement Learning
by: Deihim, Azad, et al.
Published: (2025)
by: Deihim, Azad, et al.
Published: (2025)
Learning Incentive Structures for Cooperative Resilience in Multi-Agent Systems under Social Dilemmas
by: Chacon-Chamorro, Manuela, et al.
Published: (2026)
by: Chacon-Chamorro, Manuela, et al.
Published: (2026)
Multi-Agent Model-Based Reinforcement Learning with Joint State-Action Learned Embeddings
by: Wang, Zhizun, et al.
Published: (2026)
by: Wang, Zhizun, et al.
Published: (2026)
Mini Honor of Kings: A Lightweight Environment for Multi-Agent Reinforcement Learning
by: Liu, Lin, et al.
Published: (2024)
by: Liu, Lin, et al.
Published: (2024)
Optimistic ε-Greedy Exploration for Cooperative Multi-Agent Reinforcement Learning
by: Zhang, Ruoning, et al.
Published: (2025)
by: Zhang, Ruoning, et al.
Published: (2025)
G-Designer: Architecting Multi-agent Communication Topologies via Graph Neural Networks
by: Zhang, Guibin, et al.
Published: (2024)
by: Zhang, Guibin, et al.
Published: (2024)
T2MAC: Targeted and Trusted Multi-Agent Communication through Selective Engagement and Evidence-Driven Integration
by: Sun, Chuxiong, et al.
Published: (2024)
by: Sun, Chuxiong, et al.
Published: (2024)
Multi-Agent Craftax: Benchmarking Open-Ended Multi-Agent Reinforcement Learning at the Hyperscale
by: Omari, Bassel Al, et al.
Published: (2025)
by: Omari, Bassel Al, et al.
Published: (2025)
Finding the Weakest Link: Adversarial Attack against Multi-Agent Communications
by: Standen, Maxwell, et al.
Published: (2026)
by: Standen, Maxwell, et al.
Published: (2026)
Conformal Off-Policy Prediction for Multi-Agent Systems
by: Kuipers, Tom, et al.
Published: (2024)
by: Kuipers, Tom, et al.
Published: (2024)
Similar Items
-
Learning Multi-Agent Communication from Graph Modeling Perspective
by: Hu, Shengchao, et al.
Published: (2024) -
Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency
by: Zhang, Qixin, et al.
Published: (2025) -
Effective Policy Learning for Multi-Agent Online Coordination Beyond Submodular Objectives
by: Zhang, Qixin, et al.
Published: (2025) -
Cut the Crap: An Economical Communication Pipeline for LLM-based Multi-Agent Systems
by: Zhang, Guibin, et al.
Published: (2024) -
Fully Independent Communication in Multi-Agent Reinforcement Learning
by: Pina, Rafael, et al.
Published: (2024)