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Muhammad A Rahman

2 accepted papers

2021

Scaling Multi-Agent Reinforcement Learning with Selective Parameter Sharing

ICML 2021spotlight

Sharing parameters in multi-agent deep reinforcement learning has played an essential role in allowing algorithms to scale to a large number of agents. Parameter sharing between agents significantly decreases the number of trainable parameters, shortening training times to tractable levels, and has…

2021

Towards Open Ad Hoc Teamwork Using Graph-based Policy Learning

ICML 2021spotlight

Ad hoc teamwork is the challenging problem of designing an autonomous agent which can adapt quickly to collaborate with teammates without prior coordination mechanisms, including joint training. Prior work in this area has focused on closed teams in which the number of agents is fixed. In this work,…