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cs.MA2025
GAWM: Global-Aware World Model for Multi-Agent Reinforcement Learning
Zifeng Shi, Meiqin Liu, Senlin Zhang +3
In recent years, Model-based Multi-Agent Reinforcement Learning (MARL) has demonstrated significant advantages over model-free methods in terms of sample efficiency by using indepe…
cs.MA2024
RMIO: A Model-Based MARL Framework for Scenarios with Observation Loss in Some Agents
Zifeng Shi, Meiqin Liu, Senlin Zhang +2
In recent years, model-based reinforcement learning (MBRL) has emerged as a solution to address sample complexity in multi-agent reinforcement learning (MARL) by modeling agent-env…