Soft constraints extend classical constraints, represent multiple consistency levels, and provide a way to express preferences, fuzziness, and uncertainty. This paper addresses a concurrent programming framework where soft constraints can be handled. The authors show how the classical concurrent constraint (cc) programming framework can work with soft constraints, and present an extension of cc languages that use soft constraints to prune and direct the search for solutions to constraint satisfaction problems. The new programming paradigm, called soft cc (scc), can be useful in Web-related scenarios. In particular, scc allows Web agents to express interaction/negotiation protocols, and to post preference requests, such that the underlying soft constraint solver can find agreement among the agents even in the presence of incompatible requests.

This very technical paper uses computational theory and its related mathematics to build a solid framework for the soft concurrent constraint environment. The contents of the paper include: a broad introduction; background on concurrent constraint programming and soft constraints, separately; concurrent constraint programming over soft constraints; a revision of syntax and semantics to fully address soft concurrent constraint programming; notions related to optimization, success, and failure; an example application scenario related to networks; and a brief section pointing out the main results and possible future work.

The paper is very carefully written and organized, but it is intended for the serious reader only. Careful attention was paid to layout, and to the effective use of figures to illustrate key points. The intended audience is primarily researchers in concurrent programming who have an interest in extending classical concurrent constraint programming to include soft concurrent constraints.