WHEN IS NONADAPTIVE INFORMATION AS POWERFUL AS ADAPTIVE INFORMATION? .

J. F. Traub; G. W. Wasilkowski; H. Wozniakowski

doi:10.1109/cdc.1984.272339

WHEN IS NONADAPTIVE INFORMATION AS POWERFUL AS ADAPTIVE INFORMATION? .

J. F. Traub, G. W. Wasilkowski, H. Wozniakowski

Computer Science

Research output: Contribution to journal › Conference article › peer-review

2 Scopus citations

Abstract

Information based complexity is a unified treatment of problems where only partial or approximate information is available. In this approach one states how well a problem should be solved and indicates the type of information available. The theory then tells one optimal information and optimal algorithm and yields bounds on the problem complexity. Recent results addressing one of the problems studied in information based complexity are surveyed. The problem deals with nonadaptive and adaptive information both for the worst case and average case settings.

Original language	English
Pages (from-to)	1536-1540
Number of pages	5
Journal	Proceedings of the IEEE Conference on Decision and Control
DOIs	https://doi.org/10.1109/cdc.1984.272339
State	Published - 1984

ASJC Scopus subject areas

Control and Systems Engineering
Modeling and Simulation
Control and Optimization

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10.1109/cdc.1984.272339

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abstract = "Information based complexity is a unified treatment of problems where only partial or approximate information is available. In this approach one states how well a problem should be solved and indicates the type of information available. The theory then tells one optimal information and optimal algorithm and yields bounds on the problem complexity. Recent results addressing one of the problems studied in information based complexity are surveyed. The problem deals with nonadaptive and adaptive information both for the worst case and average case settings.",

author = "Traub, {J. F.} and Wasilkowski, {G. W.} and H. Wozniakowski",

year = "1984",

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AU - Wasilkowski, G. W.

AU - Wozniakowski, H.

PY - 1984

Y1 - 1984

N2 - Information based complexity is a unified treatment of problems where only partial or approximate information is available. In this approach one states how well a problem should be solved and indicates the type of information available. The theory then tells one optimal information and optimal algorithm and yields bounds on the problem complexity. Recent results addressing one of the problems studied in information based complexity are surveyed. The problem deals with nonadaptive and adaptive information both for the worst case and average case settings.

AB - Information based complexity is a unified treatment of problems where only partial or approximate information is available. In this approach one states how well a problem should be solved and indicates the type of information available. The theory then tells one optimal information and optimal algorithm and yields bounds on the problem complexity. Recent results addressing one of the problems studied in information based complexity are surveyed. The problem deals with nonadaptive and adaptive information both for the worst case and average case settings.

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WHEN IS NONADAPTIVE INFORMATION AS POWERFUL AS ADAPTIVE INFORMATION? .

Abstract

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