Shaul Markovitch

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Shaul Markovitch, an Israeli computer scientist, AI researcher, and faculty member in the Computer Science department at Technion - Israel Institute of Technology. His research covers machine learning and AI with the topics selective learning, speedup learning, feature generation, active learning, learning in multi-agent systems, opponent modeling, game playing, anytime algorithms, resource-bounded reasoning, reasoning under uncertainty, and heuristic search .

=Photos= Shaul Markovitch talks on How Computers Play Chess at the Man vs Machine Symposium, University of Haifa, October 2002

=Selected Publications=

1990 ...

 * Shaul Markovitch, Yaron Sella (1993). Learning of Resource Allocation Strategies for Game Playing. International Joint Conference on Artificial Intelligence, pdf
 * David Carmel, Shaul Markovitch (1993). Learning Models of Opponent's Strategy in Game Playing. [[Conferences#AAAI-93|AAAI 1993], FS-93-02, pdf
 * David Carmel, Shaul Markovitch (1994). ''The M* Algorithm: Incorporating Opponent Models into Adversary Search'. CIS Report #9402, pdf
 * David Carmel, Shaul Markovitch (1996). Incorporating Opponent Models into Adversary Search. AAAI 1996, pdf
 * Lev Finkelstein, Shaul Markovitch (1998). Learning to Play Chess Selectively by Acquiring Move Patterns. ICCA Journal, Vol. 21, No. 2, pdf
 * Lev Finkelstein, Shaul Markovitch (1998). A Selective Macro-learning Algorithm and its Application to the NxN Sliding-Tile Puzzle. JAIR, Vol. 8, arXiv:cs/9806102

2000 ...

 * Shaul Markovitch (2002). Tutorial: How Computers Play Chess. Man vs Machine Symposium
 * Lev Finkelstein, Shaul Markovitch, Ehud Rivlin (2003). Optimal Schedules for Parallelizing Anytime Algorithms: The Case of Shared Resources. JAIR, Vol. 19, arXiv:1106.5269

=External Links=
 * Shaul Markovitch's Home Page
 * Shaul Markovitch - Google Scholar Citations
 * Shaul Markovitch - YouTube
 * Shaul Markovitch, Ziv Cohen, Peer Sagiv, Ilya Smagloy - Shine On You Crazy Diamond, Technion, November 04, 2019, YouTube Video

=References= Up one level