Constraint Processing Offers Improved Expressiveness and Inference for Interactive Expert Systems

摘要

Expert systems constitute one of the most successful application areas for Artificial Intelligence techniques; they have been deployed in many areas of industry and commerce. If-then rules are the core knowledge representation technology in currently deployed systems. However, if we replace rules by constraints, we get improved expressiveness in knowledge representation and richer inference.