Lempel-Ziv Coding in Reinforcement Learning

Authors:
Kazunori Iwata;Naohiro Ishii
Affiliations:
-;-
Venue:
IDEAL '02 Proceedings of the Third International Conference on Intelligent Data Engineering and Automated Learning
Year:
2002

Citing 5
Cited 0

Technical Note: \cal Q-Learning

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Abstract

In this paper, we propose a new measure within the framework of reinforcement learning, by describing a model of an information source as a representation of a learning process. We confirm in experiments that Lempel-Ziv coding for a string of episode sequences provides a quality measure to describe the degree of complexity for learning. In addition, we discuss functions comparing expected return and its variance.