Coordination-driven learning in multi-agent problem spaces

2018-09-13 · Sean L. Barton, Nicholas R. Waytowich, Derrik E. Asher

We discuss the role of coordination as a direct learning objective in multi-agent reinforcement learning (MARL) domains. To this end, we present a novel means of quantifying coordination in multi-agent systems, and discuss the implications of using such a measure to optimize coordinated agent policies. This concept has important implications for adversary-aware RL, which we take to be a sub-domain of multi-agent learning.

📄 PDF Abstract BibTeX arXiv:1809.04918

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Multi-agent Reinforcement Learning reinforcement-learning Reinforcement Learning Reinforcement Learning (RL)

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