TDLeaf(lambda): Combining Temporal Difference Learning with Game-Tree Search
Abstract
In this paper we present TDLeaf(lambda), a variation on the TD(lambda) algorithm that enables it to be used in conjunction with minimax search. We present some experiments in both chess and backgammon which demonstrate its utility and provide comparisons with TD(lambda) and another less radical variant, TD-directed(lambda). In particular, our chess program, ``KnightCap,'' used TDLeaf(lambda) to learn its evaluation function while playing on the Free Internet Chess Server (FICS, fics.onenet.net). It improved from a 1650 rating to a 2100 rating in just 308 games. We discuss some of the reasons for this success and the relationship between our results and Tesauro's results in backgammon.
Cite
@article{arxiv.cs/9901001,
title = {TDLeaf(lambda): Combining Temporal Difference Learning with Game-Tree Search},
author = {Jonathan Baxter and Andrew Tridgell and Lex Weaver},
journal= {arXiv preprint arXiv:cs/9901001},
year = {2007}
}
Comments
5 pages. Also in Proceedings of the Ninth Australian Conference on Neural Networks (ACNN'98), Brisbane QLD, February 1998, pages 168-172