Csaba Szepesvári

From Chessprogramming wiki
Jump to: navigation, search

Home * People * Csaba Szepesvári

Csaba Szepesvári [1]

Csaba Szepesvári,
a Hungarian computer scientiest with research interests in applications of statistical techniques in AI, and Reinforcement Learning [2]. Csaba Szepesvári worked at the Computer and Automation Research Institute of the Hungarian Academy of Sciences, and is professor at the Department of Computing Science, University of Alberta, and principal investigator of the RLAI [3] group, actually on leave at DeepMind.


In 2006, along with Levente Kocsis, Csaba Szepesvári introduced UCT (Upper Confidence bounds applied to Trees), a new algorithm that applies bandit ideas to guide Monte-Carlo planning [4]. UCT accelerated the Monte-Carlo revolution in computer Go [5] and other domains.

Selected Publications

[6] [7]

1994 ...

2005 ...

2010 ...

2015 ...

External Links


Up one level