Coordination-driven learning in multi-agent problem spaces

Barton, Sean L., Waytowich, Nicholas R., Asher, Derrik E.

arXiv.org Artificial Intelligence 

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.