Representation Discovery for Kernel-Based Reinforcement Learning
Recent years have seen increased interest in non-parametric reinforcement learning. There are now practical kernel-based algorithms for approximating value functions; however, kernel regression requires that the underlying function being approximated be smooth on its domain. Few problems of interest...
Main Authors: | , |
---|---|
Other Authors: | |
Published: |
2015
|
Subjects: | |
Online Access: | http://hdl.handle.net/1721.1/100053 |