Coordination-driven learning in multi-agent problem spaces Article Swipe
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Sean L. Barton
,
Nicholas R. Waytowich
,
Derrik E. Asher
·
YOU?
·
· 2018
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.1809.04918
· OA: W2890581300
YOU?
·
· 2018
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.1809.04918
· OA: W2890581300
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.
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