Breaking the mold: The challenge of large scale MARL specialization
<|reference_start|>Breaking the mold: The challenge of large scale MARL specialization: In multi-agent learning, the predominant approach focuses on generalization, often neglecting the optimization of individual agents. This emphasis on generalization limits the ability of agents to utilize their unique strengths, resulting in inefficiencies. This paper introduces Comparative Advantage Maximization (CAM), a method designed to enhance individual agent specialization in multiagent systems. CAM employs a two-phase process, combining centralized population training with individual specialization through comparative advantage maximization. CAM achieved a 13.2% improvement in individual agent performance and a 14.9% increase in behavioral diversity compared to state-of-the-art systems. The success of CAM highlights the importance of individual agent specialization, suggesting new directions for multi-agent system development.<|reference_end|>
@article{juang2024breaking,
    title={Breaking the mold: The challenge of large scale MARL specialization},
    author={Stefan Juang, Hugh Cao, Arielle Zhou, Ruochen Liu, Nevin L. Zhang and
  Elvis Liu},
    journal={arXiv preprint arXiv:2410.02128},
    year={2024},
    archivePrefix={arXiv},
    eprint={2410.02128},
    primaryClass={cs.LG}
}