Preference programming: Advanced problem solving for configuration

• Authors: Ulrich Junker;Daniel Mailharro
• Venue: Artificial Intelligence for Engineering Design, Analysis and Manufacturing
• Year: 2003

Configuration problems often involve large product catalogs, and the given user requests can be met by many different kinds of parts from this catalog. Hence, configuration problems are often weakly constrained and have many solutions. However, many of those solutions may be discarded by the user as long as more interesting solutions are possible. The user often prefers certain choices to others (e.g., a red color for a car to a blue color) or prefers solutions that minimize or maximize certain criteria such as price and quality. In order to provide satisfactory solutions, a configurator needs to address user preferences and user wishes. Another important problem is to provide high-level features to control different reasoning tasks such as solution search, explanation, consistency checking, and reconfiguration. We address those problems by introducing a preference programming system that provides a new paradigm for expressing user preferences and user wishes and provides search strategies in a declarative and unified way, such that they can be embedded in a constraint and rule language. The preference programming approach is completely open and dynamic. In fact, preferences can be assembled from different sources such as business rules, databases, annotations of the object model, or user input. An advanced topic is to elicit preferences from user interactions, especially from explanations of why a user rejects proposed choices. Our preference programming system has successfully been used in different configuration domains such as loan configuration, service configuration, and other problems.