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Constructing Abstraction Hierarchies Using a Skill-Symbol Loop

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Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence. Pages 1648-1653.

Abstract

We describe a framework for building abstraction hierarchies whereby an agent alternates skill- and representation-construction phases to construct a sequence of increasingly abstract Markov decision processes. Our formulation builds on recent results showing that the appropriate abstract representation of a problem is specified by the agent's skills. We describe how such a hierarchy can be used for fast planning, and illustrate the construction of an appropriate hierarchy for the Taxi domain.

George Dimitri Konidaris. 2016. Constructing Abstraction Hierarchies Using a Skill-Symbol Loop. In Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, IJCAI-16. IJCAI, 1648–1653. https://ijcai.org/proceedings/2016/236
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