Tractability-preserving Transformations of Global Cost Functions - LIRMM - Laboratoire d’Informatique, de Robotique et de Microélectronique de Montpellier Access content directly
Journal Articles Artificial Intelligence Year : 2016

Tractability-preserving Transformations of Global Cost Functions


Graphical model processing is a central problem in artificial intelligence. The optimization of the combined cost of a network of local cost functions federates a variety of famous problems including CSP, SAT and Max-SAT but also optimization in stochastic variants such as Markov Random Fields and Bayesian networks. Exact solving methods for these problems typically include branch and bound and local inference-based bounds.In this paper we are interested in understanding when and how dynamic programming based optimization can be used to efficiently enforce soft local consistencies on Global Cost Functions, defined as parameterized families of cost functions of unbounded arity. Enforcing local consistencies in cost function networks is performed by applying so-called Equivalence Preserving Transformations (EPTs) to the cost functions. These EPTs may transform global cost functions and make them intractable to optimize.We identify as tractable projection-safe those global cost functions whose optimization is and remains tractable after applying the EPTs used for enforcing arc consistency. We also provide new classes of cost functions that are tractable projection-safe thanks to dynamic programming.We show that dynamic programming can either be directly used inside filtering algorithms, defining polynomially DAG-filterable cost functions, or emulated by arc consistency filtering on a Berge-acyclic network of bounded-arity cost functions, defining Berge-acyclic network-decomposable cost functions. We give examples of such cost functions and we provide a systematic way to define decompositions from existing decomposable global constraints.These two approaches to enforcing consistency in global cost functions are then embedded in a solver for extensive experiments that confirm the feasibility and efficiency of our proposal.
Fichier principal
Vignette du fichier
tractability-preserving-transformations.pdf (536.92 Ko) Télécharger le fichier
Origin Files produced by the author(s)

Dates and versions

lirmm-01374533 , version 1 (30-09-2016)




David Allouche, Christian Bessiere, Patrice Boizumault, Simon de Givry, Patricia Gutierrez, et al.. Tractability-preserving Transformations of Global Cost Functions. Artificial Intelligence, 2016, 238, pp.166-189. ⟨10.1016/j.artint.2016.06.005⟩. ⟨lirmm-01374533⟩
358 View
234 Download



Gmail Mastodon Facebook X LinkedIn More