2 papers
cs.MA2025
Making Teams and Influencing Agents: Efficiently Coordinating Decision Trees for Interpretable Multi-Agent Reinforcement Learning
Rex Chen, Stephanie Milani, Zhicheng Zhang +2
Poor interpretability hinders the practical applicability of multi-agent reinforcement learning (MARL) policies. Deploying interpretable surrogates of uninterpretable policies enha…
cs.LG2024
MESA: Cooperative Meta-Exploration in Multi-Agent Learning through Exploiting State-Action Space Structure
Zhicheng Zhang, Yancheng Liang, Yi Wu +1
Multi-agent reinforcement learning (MARL) algorithms often struggle to find strategies close to Pareto optimal Nash Equilibrium, owing largely to the lack of efficient exploration.…