The Collection of
Computer Science Bibliographies

Bibliography on Machine Learning in Strategic Game Playing

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Number of references:486Last update:November 7, 2003
Number of online publications:221Supported:yes
Most recent reference:October 2002

Information on the Bibliography

Johannes Fürnkranz <juffi @ ai . univie . ac . at> (email mangled to prevent spamming)
Österreichisches Forschungsinstitut für Artificial Intelligence (ÖFAI)
Schottengasse 3
A-1010 Vienna
This bibliography contains a variety of references concerning Machine Learning in Strategic Game Playing, i.e. on ideas how game playing programs can improve their play by learning from their own or others' experience. Included in the list are only references in which the application of a Machine Learning algorithm to a game playing problem forms a considerable part of the paper. Papers in Machine Learning that might be relevant for the problem, but not explicitly address game playing (like Sutton's paper on Temporal Difference Learning) have not been included. Likewise, papers that describe a game playing application that might be relevant for Machine Learning methods (like Wilkins's paper on PARADISE) have been omitted.
machine learning, strategic game playing, Chess, Checkers, Othello, Go, Go-Moku, Backgammon, Abalone, Connect-Four
Author Comments:
I am interested in all references to on-line or off-line ressources on this topic. If you happen to know anything that I seem to be unaware of please let me know!.
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Browsing the bibliography

Bibliographic Statistics

inproceedings(205), article(117), incollection(69), techreport(33), mastersthesis(22), phdthesis(18), misc(11), book(9), proceedings(2)
title(486), available(485), year(484), author(482), game(438), learning(390), pages(315), booktitle(274), address(221), url(217), publisher(187), editor(171), volume(131), journal(117), number(115), month(64), note(57), school(40), institution(34), series(23), chapter(18), organization(13), howpublished(6), type(4), edition(1), issue(1), publichser(1)
Distribution of publication dates:
Distribution of publication dates

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