Compilation de CSPs : carte de complexité des MDDs non-déterministes

National audienceLes CSPs fournissent un cadre puissant pour la représentation de problèmes très divers. La difficulté est que la plupart des requêtes associées aux CSPs sont NP-difficiles, mais doivent dans certains contextes être traitées « en ligne ». C’est pour cette raison que les diagrammes de décision multivalués (MDDs) ont été proposés pour la compilation de CSPs. Cet article dresse une carte de compilation des MDDs, dans l’esprit de la carte de la famille des NNFs de Darwiche et Marquis, en analysant les MDDs selon leur compacité et les requêtes et transformations qu’ils supportent en temps polynomial. Les MDDs déterministes et ordonnés généralisant les diagrammes de décision binaire ordonnes à des variables non-booléennes, le fait que leurs propriétés soient similaires n’est pas surprenant. Cependant, notre étude met en avant l’intérêt des MDDs ordonnes non déterministes : restreint aux variables booléennes, ce fragment est strictement plus compact que ceux des OBDDs et des DNFs, et admet des performances proches de celles des DNNFs. La comparaison aux MDDs classiques montre que relâcher la contrainte du déterminisme améliore la compacité et permet a plus de transformations d’être supportées en temps polynomial. Des expériences sur des problèmes aléatoires confirment le gain en compacité

Compiling CSPs: A Complexity Map of (Non-Deterministic) Multivalued Decision Diagrams

International audienceConstraint Satisfaction Problems (CSPs) offer a powerful framework for representing a great variety of problems. The difficulty is that most of the requests associated with CSPs are NP-hard. When these requests have to be addressed online, Multivalued Decision Diagrams (MDDs) have been proposed as a way to compile CSPs. In the present paper, we draw a compilation map of MDDs, in the spirit of the NNF compilation map, analyzing MDDs according to their succinctness and to their tractable transformations and queries. Deterministic ordered MDDs are a generalization of ordered binary decision diagrams to non-Boolean domains: unsurprisingly, they have similar capabilities. More interestingly, our study puts forward the interest of non-deterministic ordered MDDs: when restricted to Boolean domains, they capture OBDDs and DNFs as proper subsets and have performances close to those of DNNFs. The comparison to classical, deterministic MDDs shows that relaxing the determinism requirement leads to an increase in succinctness and allows more transformations to be satisfied in polynomial time (typically, the disjunctive ones). Experiments on random problems confirm the gain in succinctness

The role of the agent's outside options in principal-agent relationships

We consider a principal-agent model of adverse selection where, in order to trade with the principal, the agent must undertake a relationship-specific investment which affects his outside option to trade, i.e. the payoff that he can obtain by trading with an alternative principal. This creates a distinction between the agent’s ex ante (before investment) and ex post (after investment) outside options to trade. We investigate the consequences of this distinction, and show that whenever an agent’s ex ante and ex post outside options differ, this may equip the principal with an additional tool for screening among different agent types, by randomizing over the probability with which trade occurs once the agent has undertaken the investment. In turn, this may enhance the efficiency of the optimal second-best contract

Variable and value elimination in binary constraint satisfaction via forbidden patterns

Variable or value elimination in a constraint satisfaction problem (CSP) can be used in preprocessing or during search to reduce search space size. A variable elimination rule (value elimination rule) allows the polynomial-time identification of certain variables (domain elements) whose elimination, without the introduction of extra compensatory constraints, does not affect the satisfiability of an instance. We show that there are essentially just four variable elimination rules and three value elimination rules defined by forbidding generic sub-instances, known as irreducible existential patterns, in arc-consistent CSP instances. One of the variable elimination rules is the already-known Broken Triangle Property, whereas the other three are novel. The three value elimination rules can all be seen as strict generalisations of neighbourhood substitution.Comment: A full version of an IJCAI'13 paper to appear in Journal of Computer and System Sciences (JCSS

Global Inverse Consistency for Interactive Constraint Satisfaction

International audienceSome 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

Constraint solving in uncertain and dynamic environments - a survey

International audienceThis article follows a tutorial, given by the authors on dynamic constraint solving at CP 2003 (Ninth International Conference on Principles and Practice of Constraint Programming) in Kinsale, Ireland. It aims at offering an overview of the main approaches and techniques that have been proposed in the domain of constraint satisfaction to deal with uncertain and dynamic environments

Complexity of Minimum Biclique Decomposition of Bipartite Graphs

Many problems studied in graph theory are graph decomposition problems. The minimum number of complete bipartite graphs needed to partition the edges of a bipartite graph. is one of these problem and it is still open. We propose a NP-completness proof for its decision version and we show that it is polynomial on bipartite C4-free graphs

Consistency restoration and explanations in dynamic CSP- application to configuration (In Notes of the ECAI-2000 Workshop on modelling and solving problems with constraints)

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Explications et aide à la restauration de la cohérence dans les CSP interactifs : application à la configuration

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Handling interactivity in a constraint-based approach of configuration (In Notes of the ECAI-2000 Workshop on configuration)

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