Sample-efficient Cross-Entropy Method for Real-time Planning
Published in Arxiv, 2020
Arxiv
Authors: Cristina Pinneri, Shambhuraj Sawant, Sebastian Blaes, Jan Achterhold, Joerg Stueckler, Michal Rolínek, Georg Martius
Cross-Entropy method is a powerful optimizer for model-based RL. But it is too slow for real time deployment. We introduce several adjustments and tricks to bridge the “real time” gap. The resulting iCEM is FAAAAST!
Links: Arxiv
[1/6] How many random planning trajectories (30 steps ahead) do I need to get this behavior?
— Georg Martius (@GMartius) August 19, 2020
Surprisingly little!
See our newest paper on making CEM efficient: https://t.co/2XKmF5bQSw
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