AINeutralarXiv – CS AI · 4h ago6/10
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GCT-MARL: Graph-Based Contrastive Transfer for Sample-Efficient Cooperative Multi-Agent Reinforcement Learning
Researchers introduce GCT-MARL, a transfer learning framework for multi-agent reinforcement learning that enables faster training across different environments by combining graph-based contrastive learning with adaptive alignment techniques. The method demonstrates significant convergence improvements over from-scratch training in both homogeneous and heterogeneous agent scenarios, while supporting continual learning across sequential tasks.