Skill Characterization Based on Betweenness

Part of Advances in Neural Information Processing Systems 21 (NIPS 2008)

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Özgür Şimşek, Andrew Barto


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.