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title
Learning Latent Plans from Play
description
Latent robotic plans are learned from unlabeled play data.
site name
Latent robotic plans are learned from unlabeled play data.
author
updated
2025-12-16 16:54:37
raw text
Learning Latent Plans from Play Learning Latent Plans from Play scroll down Learning Latent Plans from Play Corey Lynch Google Brain Mohi Khansari Google X Ted Xiao Google Brain Vikash Kumar Google Brain Jonathan Tompson Google Brain Sergey Levine Google Brain Pierre Sermanet Google Brain March 5 2019 Download PDF Abstract We propose learning from teleoperated play data as a way to scale up multi-task robotic skill learning. Learning from play (LfP) offers three main advantages: 1) It is cheap . Large amounts of play data can be collected quickly as it does not require scene staging, task segmenting, or resetting to an initial state. 2) It is general . It contains both functional and non-functional behavior, relaxing the need for a predefined task distribution. 3) It is rich . Play involves repeated, varied behavior and naturally leads to high coverage of the possible interaction space. These properties distinguish play from expert de...
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