Multi-Agent Reinforcement Learning Comparison Hub
4 papers - avg viability 4.8
Top Papers
- Contextual Counterfactual Credit Assignment for Multi-Agent Reinforcement Learning in LLM Collaboration(7.0)
C3 isolates the causal impact of individual messages in cooperative multi-agent LLM systems, improving credit assignment and terminal performance.
- Distributionally Robust Cooperative Multi-Agent Reinforcement Learning via Robust Value Factorization(6.0)
Enhance multi-agent systems with robust decision-making for real-world uncertainties using DrIGM principle.
- EcoFair-CH-MARL: Scalable Constrained Hierarchical Multi-Agent RL with Real-Time Emission Budgets and Fairness Guarantees(3.0)
EcoFair-CH-MARL is a framework for efficient and equitable maritime logistics using multi-agent reinforcement learning.
- MA-VLCM: A Vision Language Critic Model for Value Estimation of Policies in Multi-Agent Team Settings(3.0)
MA-VLCM enhances multi-agent reinforcement learning by using a pretrained vision-language model as a centralized critic for improved sample efficiency.