Stuart Russell

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Stuart Russell [1]

Stuart J. Russell,
a British computer scientist, professor and chair of Computer Science, Lotfi A. Zadeh chair in Engineering, and Director, Center for Intelligent Systems, Computer Science Division, University of California, Berkeley, California. He received his B.A. with first-class honors in physics from Oxford University in 1982, and his Ph.D. in Computer Science from Stanford in 1986. He is also an adjunct professor of Neurological Surgery at UC San Francisco. He is a Fellow and former Executive Council member of the AAAI and a fellow of the ACM. His research covers a wide range of topics in artificial intelligence including machine learning, probabilistic reasoning, knowledge representation, planning, real-time decision making, multitarget tracking, and computer vision [2] .

Optimal Game-Tree Search

Abstract from Stuart Russell, Eric Wefald (1989). On optimal game-tree search using rational metareasoning [3]:

In this paper we outline a general approach to the study of problem-solving, in which search steps are considered decisions in the same sense as actions in the world. Unlike other metrics in the literature, the value of a search step is defined as a real utility rather than as a quasi-utility, and can therefore be computed directly from a model of the base-level problem-solver. We develop a formula for the expected value of a search step in a game-playing context using the single-step assumption, namely that a computation step can be evaluated as it was the last to be taken. We prove some meta-level theorems that enable the development of a low-overhead algorithm, MGSS*, that chooses search steps in order of highest estimated utility. Although we show that the single-step assumption is untenable in general, a program implemented for the game of Othello soundly beats an alpha-beta search while expanding significantly fewer nodes, even though both programs use the same evaluation function. 

Selected Publications

[4] [5] [6]

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External Links


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