A Maximal Tractable Class of Soft Constraints
نویسندگان
چکیده
Many optimization problems can be expressed using some form of soft constraints, where different measures of desirability are associated with different combinations of domain values for specified subsets of variables. In this paper we identify a class of soft binary constraints for which the problem of finding the optimal solution is tractable. In other words, we show that for any given set of such constraints, there exists a polynomial time algorithm to determine the assignment having the best overall combined measure of desirability. This tractable class includes many commonly-occurring soft constraints, such as “as near as possible” or “as soon as possible after”, as well as crisp constraints such as “greater than”.
منابع مشابه
A Maximal Tractable Class of Soft Constraints A Maximal Tractable Class of Soft Constraints∗
Many researchers in artificial intelligence are beginning to explore the use of soft constraints to express a set of (possibly conflicting) problem requirements. A soft constraint is a function defined on a collection of variables which associates some measure of desirability with each possible combination of values for those variables. However, the crucial question of the computational complex...
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