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Published Articles >> Table of Contents >> Abstract
IEEE/WIC International Conference on Intelligent Agent Technology (IAT'03)
p. 203
Problem-solving in open environments
Santiago Macho-Gonzalez, Swiss Federal Institute of Technology (EPFL)
Boi Faltings, Swiss Federal Institute of Technology (EPFL)
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DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/IAT.2003.1241069
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| Abstract |
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With the increasing use of the internet, many problem-solving
tasks such as resource allocation, scheduling, planning,
and configuration pose themselves in an open setting
involving multiple participants. Existing search-based
problem-solving techniques are based on the closed-world
assumption and require that all options be collected before
problem-solving can start. This approach of turning the web
into a virtual database often leads to gathering much more
information than necessary to solve the problem.
We consider constraint satisfaction as the most successful
practical problem solving technique, and define open
constraint satisfaction where values are incrementally gathered
during problem solving. We present several algorithms
for open constraint satisfaction and show that on random
problems, they require gathering significantly less values.
We then extend the technique to constraint optimization using
the fuzzy CSP model, and show that here too great efficiency
gains can be achieved by coupling problem solving
and information gathering.
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 Additional Information
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Citation:
Santiago Macho-Gonzalez, Boi Faltings,
"Problem-solving in open environments,"
iat,
p. 203,
IEEE/WIC International Conference on Intelligent Agent Technology (IAT'03),
2003
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