A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf
.
Efficient Skill Learning using Abstraction Selection
2009
International Joint Conference on Artificial Intelligence
We present an algorithm for selecting an appropriate abstraction when learning a new skill. We show empirically that it can consistently select an appropriate abstraction using very little sample data, and that it significantly improves skill learning performance in a reasonably large real-valued reinforcement learning domain.
dblp:conf/ijcai/KonidarisB09
fatcat:bphg3b2igrgtjc6wciit23u3ki