Option Discovery in Hierarchical Reinforcement Learning using Spatio-Temporal Clustering

This paper introduces an automated skill acquisition framework in reinforcement learning which involves identifying a hierarchical description of the given task in terms of abstract states and extended actions between abstract states. Identifying such structures present in the task provides ways to...

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Veröffentlicht in:	arXiv.org 2020-09
Hauptverfasser:	Srinivas, Aravind, Krishnamurthy, Ramnandan, Kumar, Peeyush, Ravindran, Balaraman
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Clustering Machine learning Metastable region Skills Task complexity
Online-Zugang:	Volltext
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