arXiv (OAI Expanded)
open access
Privileged observations enable rapid and reliable policy discovery directly in the physical world
We study how privileged information about a physical system affects the discovery of high-performing policies when training a reinforcement learning agent directly in the physical world. We let the agent control a cylinder in a tabletop water channel to maximize or minimize drag. The flow is chaotic
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