DocumentCode :
929207
Title :
Temporal-difference methods and Markov models
Author :
Barnard, Etienne
Author_Institution :
Dept. of Electron. & Comput. Eng., Pretoria Univ., South Africa
Volume :
23
Issue :
2
fYear :
1993
Firstpage :
357
Lastpage :
365
Abstract :
The relation between temporal-difference training methods and Markov models is explored. This relation is derived from a new perspective, and in this way the particular association between conventional temporal-difference methods and first-order Markov models is explained. The authors then derive a generalization of temporal-difference methods that is suitable for Markov models of higher order. Several issues related to the performance of mismatched temporal-difference methods (i.e., the performance when the temporal-difference method is not specifically designed to match the order of the Markov model) are investigated numerically
Keywords :
Markov processes; learning (artificial intelligence); probability; Markov models; learning; probability; temporal-difference training; Context modeling; Image recognition; Intelligent control; Learning; Numerical models; Pattern recognition; Proposals; Speech; Veins; Visual perception;
fLanguage :
English
Journal_Title :
Systems, Man and Cybernetics, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9472
Type :
jour
DOI :
10.1109/21.229449
Filename :
229449
Link To Document :
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