Subdefinite models as a variety of constraint programming

This paper describes subdefinite models as a variety of constraint satisfaction problems. The use of the method of subdefinite calculations makes it possible to solve overdetermined and underdetermined problems, as well as problems with uncertain, imprecise and incomplete data. Constraint propagation in all these problems is supported by a single data-driven inference algorithm. Several examples are given to show the capabilities of this approach for solving a wide class of problems.