The control of reasoning under uncertainty: A discussion of some programs

Paul R. Cohen

doi:10.1017/S0269888900000680

The control of reasoning under uncertainty: A discussion of some programs

Paul R. Cohen

Research output: Contribution to journal › Article › peer-review

12 Scopus citations

Abstract

This paper proposes that managing uncertainty is a control problem, a task for the control component of AI systems that decides what to do next. This view emphasizes the process of planning and executing sequences of actions that simultaneously satisfy domain goals and minimize uncertainty. The paper reviews AI systems that manage uncertainty by control. It is not an exhaustive survey, but rather illustrates issues in managing uncertainty with selected AI programs.

Original language	English (US)
Pages (from-to)	5-25
Number of pages	21
Journal	The Knowledge Engineering Review
Volume	2
Issue number	1
DOIs	https://doi.org/10.1017/S0269888900000680
State	Published - Mar 1 1987

ASJC Scopus subject areas

Software
Artificial Intelligence

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10.1017/S0269888900000680

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title = "The control of reasoning under uncertainty: A discussion of some programs",

abstract = "This paper proposes that managing uncertainty is a control problem, a task for the control component of AI systems that decides what to do next. This view emphasizes the process of planning and executing sequences of actions that simultaneously satisfy domain goals and minimize uncertainty. The paper reviews AI systems that manage uncertainty by control. It is not an exhaustive survey, but rather illustrates issues in managing uncertainty with selected AI programs.",

author = "Cohen, {Paul R.}",

note = "Funding Information: * The research was supported by DARPA-RADC Contract F30602-85-C0014 and NSF Grant IST-8409623. t This paper results from ongoing research with David Day, Jeff DeLisio, Mike Greenberg, Tom Gruber, Adele Howe, Rick Kjeldsen, Dan Suthers and Dr. Paul Berman, M.D. I am grateful for fruitful discussions with Professor Victor Lesser and Professor Glenn Shafer.",

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N2 - This paper proposes that managing uncertainty is a control problem, a task for the control component of AI systems that decides what to do next. This view emphasizes the process of planning and executing sequences of actions that simultaneously satisfy domain goals and minimize uncertainty. The paper reviews AI systems that manage uncertainty by control. It is not an exhaustive survey, but rather illustrates issues in managing uncertainty with selected AI programs.

AB - This paper proposes that managing uncertainty is a control problem, a task for the control component of AI systems that decides what to do next. This view emphasizes the process of planning and executing sequences of actions that simultaneously satisfy domain goals and minimize uncertainty. The paper reviews AI systems that manage uncertainty by control. It is not an exhaustive survey, but rather illustrates issues in managing uncertainty with selected AI programs.

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The control of reasoning under uncertainty: A discussion of some programs

Abstract

ASJC Scopus subject areas

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