Proceedings Abstracts of the Twenty-Fifth International Joint Conference on Artificial Intelligence

Constructing Abstraction Hierarchies Using a Skill-Symbol Loop / 1648
George Konidaris

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.