OpenAI Blog · Nov 7, 2018
Learning concepts with energy functions
Reviewed by Errol Vogt, Site support technician & online learning analyst · original summary · editorial policy
Learning concepts with energy functions. We’ve developed an energy-based model that can quickly learn to identify and generate instances of concepts, such as near, above, between, closest, and furthest, expressed as sets of 2d points. Our model learns these concepts after only five demonstrations. We also show cross-domain transfer: we use concepts learned in a 2d particle environment to solve tasks on a 3-dimensional physics-based robot. This update is relevant for small-office operators tracking changes in their tools.
Operator takeaway: For operators: review whether 'Learning concepts with energy functions' affects your current setup before relying on it in production.
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