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Article . 2008
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Part of book or chapter of book . 2008 . Peer-reviewed
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Timed Soft Concurrent Constraint Programs

Authors: BISTARELLI, Stefano; GABBRIELLI, Maurizio; MEO, Maria Chiara; SANTINI, Francesco;

Timed Soft Concurrent Constraint Programs

Abstract

We propose a timed and soft extension of Concurrent Constraint Programming. The time extension is based on the hypothesis of bounded asynchrony: the computation takes a bounded period of time and is measured by a discrete global clock. Action pre¯xing is then con- sidered as the syntactic marker which distinguishes a time instant from the next one. Supported by soft constraints instead of crisp ones, tell and ask agents are now equipped with a preference (or consistency) thresh- old which is used to determine their success or suspension. In the paper we provide a language to describe the agents behavior, together with its operational and denotational semantics, for which we also prove the compositionality and correctness properties. Agents negotiating Quality of Service can bene¯t from this new language, by coordinating among themselves and mediating their preferences.

Keywords

Computer programming; Concurrency control; Constraint theory; Information theory; Ketones; Linguistics; Query languages; Stabilizers (agents), Computation, Constraint Programming

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    influence
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
11
Average
Top 10%
Average
Green