Abstract
Traditionally, constraint satisfaction has been applied in closed-world scenarios, where all choices and constraints are known from the beginning and fixed. With the Internet, many of the traditional CSP applications in resource allocation, scheduling and planning pose themselves in open-world settings, where choices and constraints are to be
discovered from different servers in a network. We examine how such a distributed setting affects changes the assumptions underlying most CSP algorithms, and show how solvers can be augmented with an information gathering component that allows open-world constraint satisfaction. We report on experiments that show strong performance of such methods over others where gathering information and solving the CSP are separated.
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Faltings, B., Macho-Gonzalez, S. (2002). Open Constraint Satisfaction. In: Van Hentenryck, P. (eds) Principles and Practice of Constraint Programming - CP 2002. CP 2002. Lecture Notes in Computer Science, vol 2470. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-46135-3_24
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DOI: https://doi.org/10.1007/3-540-46135-3_24
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