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G C Konidaris and A G Barto (2009)

Efficient Skill Learning Using Abstraction Selection

In: Proceedings of the Twenty First International Joint Conference on Artificial Intelligence (IJCAI '09), ed. by C. Boutilier , pp. 107-1112.

We present an algorithm for selecting an appropriate abstraction when learning a new skill. We show empirically that it can consistently select an appro- priate abstraction using very little sample data, and that it significantly improves skill learning performance in a reasonably large real-valued reinforcement learning domain.
Reinforcement Learning; Markov Decision Processes; Semi-Markov Decision Processes; Hierarchy; Temporal Abstraction