2008
NIPS
NeurIPS 2008
Skill Characterization Based on Betweenness
Abstract
We present a characterization of a useful class of skills based on a graphical representation of an agent's interaction with its environment. Our characterization uses betweenness, a measure of centrality on graphs. It may be used directly to form a set of skills suitable for a given environment. More importantly, it serves as a useful guide for developing online, incremental skill discovery algorithms that do not rely on knowing or representing the environment graph in its entirety.
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Interdisciplinary Bridge
— Artificial Intelligence and Machine Learning and Mathematics & Optimization
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Trend Setter
— Agent Systems
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Keyword Pioneer
— graph centrality
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Reinforcement Learning
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Hot Topic Early Bird
— graph theory