Global Inverse Consistency for Interactive Constraint Satisfaction

Christian Bessiere (1) , Hélène Fargier (2, 3) , Christophe Lecoutre (4)

1 COCONUT - Agents, Apprentissage, Contraintes
2 IRIT-ADRIA - Argumentation, Décision, Raisonnement, Incertitude et Apprentissage
3 CNRS - Centre National de la Recherche Scientifique
4 CRIL - Centre de Recherche en Informatique de Lens

Some applications require the interactive resolution of a constraint problem by a human user. In such cases, it is highly desirable that the person who interactively solves the problem is not given the choice to select values that do not lead to solutions. We call this property global inverse consistency. Existing systems simulate this either by maintaining arc consistency after each assignment performed by the user or by compiling offline the problem as a multi-valued decision diagram. In this paper, we define several questions related to global inverse consistency and analyse their complexity. Despite their theoretical intractability, we propose several algorithms for enforcing global inverse consistency and we show that the best version is efficient enough to be used in an interactive setting on several configuration and design problems. We finally extend our contribution to the inverse consistency of tuples.

Mots clés: Tuples; Global inverse consistency

Domaines: Intelligence artificielle [cs.AI]; Apprentissage [cs.LG]; Logique en informatique [cs.LO]; Informatique et langage [cs.CL]

Christian Bessiere, Hélène Fargier, Christophe Lecoutre. Global Inverse Consistency for Interactive Constraint Satisfaction. CP: Principles and Practice of Constraint Programming, Sep 2013, Uppsala, Sweden. pp.159-174. ⟨hal-01147298⟩