Papers
1–4 of 4Contextual Counterfactual Credit Assignment for Multi-Agent Reinforcement Learning in LLM Collaboration
Cooperative multi-agent reinforcement learning (MARL) systems powered by large language models (LLMs) are frequently optimized via sparse terminal-only feedback. This shared signal entangles upstream ...
Distributionally Robust Cooperative Multi-Agent Reinforcement Learning via Robust Value Factorization
Cooperative multi-agent reinforcement learning (MARL) commonly adopts centralized training with decentralized execution, where value-factorization methods enforce the individual-global-maximum (IGM) p...
EcoFair-CH-MARL: Scalable Constrained Hierarchical Multi-Agent RL with Real-Time Emission Budgets and Fairness Guarantees
Global decarbonisation targets and tightening market pressures demand maritime logistics solutions that are simultaneously efficient, sustainable, and equitable. We introduce EcoFair-CH-MARL, a constr...
MA-VLCM: A Vision Language Critic Model for Value Estimation of Policies in Multi-Agent Team Settings
Multi-agent reinforcement learning (MARL) commonly relies on a centralized critic to estimate the value function. However, learning such a critic from scratch is highly sample-inefficient and often la...