From Constraints to Resolution Rules Part I : conceptual framework

: Many real world problems appear naturally as constraints satisfaction problems (CSP), for which very efficient algorithms are known. Most of these involve the combination of two techniques: some direct propagation of constraints between variables (with the goal of reducing their sets of possible values) and some kind of structured search (depth-first, breadth-first,...). But when such blind search is not possible or not allowed or when one wants a "constructive" or a "pattern-based" solution, one must devise more complex propagation rules instead. In this case, one can introduce the notion of a candidate (a "still possible" value for a variable). Here, we give this intuitive notion a well defined logical status, from which we can define the concepts of a resolution rule and a resolution theory. In order to keep our analysis as concrete as possible, we illustrate each definition with the well known Sudoku example. Part I proposes a general conceptual fram...

• Type: Conference
• Year: 2008
• Where: CISSE
• Authors: Denis Berthier
• Keywords: CISSE 2008, Complex Propagation Rules, Constraints Satisfaction Problems, Many Real World, Software Engineering