Principles of Problem Reformulation Under Uncertainty

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Citation: John S. Breese and Eric Horvitz. (1990) Principles of Problem Reformulation Under Uncertainty. In KSL-90-27, September,1990.

Publication techreport ( Edit )
type Technical Report
bibtype techreport
Bibtex basics
author John S. Breese and Eric Horvitz
title Principles of Problem Reformulation Under Uncertainty
number KSL-90-27
institution Knowledge Systems, AI Laboratory
address Stanford, CA, USA
year 1990
month September
Bibtex more
Access Paper
abstract The intelligent reformulation of a problem can greatly increase the efficiency with which that problem can be solved. However, time expended for reformulation is not available for the primary execution of the solution. Thus, under time pressure, there exists a tradeoff between the time dedicated to reformulation and the time applied to the implementation of a solution. We explore the ideal partition of resources into time dedicated to reformulation and time applied for executing the reformulated solution. We focus on the problem of determining the ideal time for dwelling on reformulation preprocessing, under conditions of uncertain knowledge about the relationship between reformulation and execution efficiency. After defining the metareasoning-partition problem under uncertainty, we identify efficient, general principles for controlling reformulation through analysis of several prototypical classes of uncertainty and utility.

KSL Technical Report ID: KSL-90-27
Facts about Principles of Problem Reformulation Under UncertaintyRDF feed
Abstract The intelligent reformulation of a problem … The intelligent reformulation of a problem can greatly increase the efficiency with which that problem can be solved. However, time expended for reformulation is not available for the primary execution of the solution. Thus, under time pressure, there exists a tradeoff between the time dedicated to reformulation and the time applied to the implementation of a solution. We explore the ideal partition of resources into time dedicated to reformulation and time applied for executing the reformulated solution. We focus on the problem of determining the ideal time for dwelling on reformulation preprocessing, under conditions of uncertain knowledge about the relationship between reformulation and execution efficiency. After defining the metareasoning-partition problem under uncertainty, we identify efficient, general principles for controlling reformulation through analysis of several prototypical classes of uncertainty and utility. ypical classes of uncertainty and utility.
Address Stanford, CA, USA  +
Author John S. Breese and Eric Horvitz  +
Bibtype techreport  +
Has author John S. Breese and Eric Horvitz  +
Has identifier KSL-90-27  +
Has publishing details September,1990  +
Has title Principles of Problem Reformulation Under Uncertainty  +
Has where published KSL-90-27  +
Has year 1990  +
Institution Knowledge Systems, AI Laboratory  +
Ksl tr id KSL-90-27  +
Month September  +
Number KSL-90-27  +
Process note NO  +
Title Principles of Problem Reformulation Under Uncertainty  +
Year 1990  +
Retrieved from "http://tw.rpi.edu/wiki/Principles_of_Problem_Reformulation_Under_Uncertainty"
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