Batch Exploration with Examples for Scalable Robotic Reinforcement Learning

IEEE Robotics and Automation Letters(2021)

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摘要
Learning from diverse offline datasets is a promising path towards learning general purpose robotic agents. However, a core challenge in this paradigm lies in collecting large amounts of meaningful data, while not depending on a human in the loop for data collection. One way to address this challenge is through task-agnostic exploration, where an agent attempts to explore without a task-specific r...
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关键词
Task analysis,Robots,Reinforcement learning,Data collection,Standards,Labeling,Visualization
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