One Policy to Control Them All: Shared Modular Policies for Agent-Agnostic Control

ICML 2020 Wenlong HuangIgor MordatchDeepak Pathak

Reinforcement learning is typically concerned with learning control policies tailored to a particular agent. We investigate whether there exists a single global policy that can generalize to control a wide variety of agent morphologies -- ones in which even dimensionality of state and action spaces changes... (read more)

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