Abstract

Constraint programming techniques are important components of intelligent systems. They constitute a declarative and efficient methodology to represent and solve many practical problems. They have been applied successfully to a number of fields, such as scheduling of air traffic, software engineering, networks security, chemistry, and biology. Despite the proved usefulness of these techniques, they are still under-utilized in real-life applications. One reason is the perceived lack of effective communication between constraint programming experts and domain practitioners about constraints, in general, and their use in decision making, in particular.