Michael Gherrity

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Michael (Mike) Gherrity, an American computer scientist and AI-researcher from the University of California, San Diego. He defended his Ph.D. in 1993 - A Game Learning Machine, elaborating on SAL (Search and Learn), his General Game Playing program. While applying a move generator, and losing if own king is captured as sole domain specific knowledge, it was the first chess program used Temporal Difference Learning. In a match of 4200 games against GNU Chess (One second per move), it started to play random moves within its two ply search plus Consistency Search, a generalized Quiescence Search, but learned to play reasonable, but still weak chess. It archived eight draws, apparently due to a repetition detection bug in GNU Chess.

=Selected Publications=
 * Michael Gherrity (1989). A Learning Algorithm for Analog, Fully Recurrent Neural Networks. IEEE IJCNN 1989
 * Richard K. Belew, Michael Gherrity (1989). Back Propagation for the Classifier System. ICGA 1989
 * Michael Gherrity (1993). A Game Learning Machine. Ph.D. thesis, University of California, San Diego, advisor Paul Kube,  pdf, pdf
 * Michael Gherrity, Paul Kube (1993). Quiescent Search is Beneficial. Technical Report CS93-289, University of California, San Diego

=Forum Posts=
 * Subject: Re: Game Learning by Mike Gherrity, ai-repository, July 1, 1994
 * DB Tweaking Between Games by Mike Gherrity, rgcc, May 13, 1997 » Kasparov versus Deep Blue 1997
 * Learning necessary for chess champion? by Mike Gherrity, rgcc, May 16, 1997

=External Links= =References= Up one level
 * Michael Gherrity Home
 * SAL from Machine Learning in Games by Jay Scott
 * The Mathematics Genealogy Project - Michael Gherrity