Model-Based Diagnosis using Structured System Descriptions

This paper presents a comprehensive approach for model-based diagnosis which includes proposals for characterizing and computing preferred diagnoses, assuming that the system description is augmented with a system structure (a directed graph explicating the interconnections between system components). Specifically, we first introduce the notion of a consequence, which is a syntactically unconstrained propositional sentence that characterizes all consistency-based diagnoses and show that standard characterizations of diagnoses, such as minimal conflicts, correspond to syntactic variations on a consequence. Second, we propose a new syntactic variation on the consequence known as negation normal form (NNF) and discuss its merits compared to standard variations. Third, we introduce a basic algorithm for computing consequences in NNF given a structured system description. We show that if the system structure does not contain cycles, then there is always a linear-size consequence in NNF which can be computed in linear time. For arbitrary system structures, we show a precise connection between the complexity of computing consequences and the topology of the underlying system structure. Finally, we present an algorithm that enumerates the preferred diagnoses characterized by a consequence. The algorithm is shown to take linear time in the size of the consequence if the preference criterion satisfies some general conditions.Comment: See http://www.jair.org/ for any accompanying file

Improving the Efficiency of Reasoning Through Structure-Based Reformulation

Abstract. We investigate the possibility of improving the efficiency of reasoning through structure-based partitioning of logical theories, combined with partitionbased logical reasoning strategies. To this end, we provide algorithms for reasoning with partitions of axioms in first-order and propositional logic. We analyze the computational benefit of our algorithms and detect those parameters of a partitioning that influence the efficiency of computation. These parameters are the number of symbols shared by a pair of partitions, the size of each partition, and the topology of the partitioning. Finally, we provide a greedy algorithm that automatically reformulates a given theory into partitions, exploiting the parameters that influence the efficiency of computation.

Aplicação de formulas não-clausais em planejamento com redes de Petri /

Orientador : Fabiano SilvaDissertação (mestrado) - Universidade Federal do Paraná, Setor de Ciencias Exatas, Programa de Pós-Graduação em Informática. Defesa: Curitiba, 2006Inclui bibliografi

Model-based monitoring and diagnosis of systems with software-extended behavior

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2005.Includes bibliographical references (p. 107-112).Model-based diagnosis of devices has largely operated on hardware systems. However, in most complex systems today, such as aerospace vehicles, automobiles and medical devices, hardware is augmented with software functions that influence the system's behavior. As these sophisticated systems are required to perform increasingly ambitious tasks. there is a growing need to ensure their robustness and safety. Prior work introduced probabilistic, hierarchical, constraint automata (PHCA), to allow compact encoding of both hardware and software behavior. The contribution of this thesis is a capability for monitoring and diagnosing software-extended systems in the presence of delayed symptoms, based on the expressive PHCA modeling formalism. Hardware models are extended to include the behavior of associated embedded software, resulting in more comprehensive diagnoses. This work introduces a novel approach that frames diagnosis over a finite time horizon as a soft constraint optimization problem (COP), which is then decomposed into independent subproblems using tree decomposition techniques. There are two advantages to this approach. First, the approach enables finite-horizon diagnosis in the presence of delayed symptoms. Second, the soft COP formulation provides convenient expressivity for encoding the PHCA models and their execution semantics, and enables the use of decomposition-based, efficient optimal constraint solvers. The solutions to the COP correspond to the most likely state trajectories of the software- extended system.(cont.) These state trajectories are enumerated and tracked within the finite receding horizon, as observations and issued commands become available. The diagnostic capability has been implemented and demonstrated on several scenarios from the aerospace and robotic domains, including vision-based rover navigation, the global metrology subsystem of the MIT SPHERES satellites, and models of the NASA New Millennium Earth Observing One (EO-1) spacecraft.by Tsoline Mikaelian.S.M

Knowledge compilation for online decision-making : application to the control of autonomous systems = Compilation de connaissances pour la décision en ligne : application à la conduite de systèmes autonomes

La conduite de systèmes autonomes nécessite de prendre des décisions en fonction des observations et des objectifs courants : cela implique des tâches à effectuer en ligne, avec les moyens de calcul embarqués. Cependant, il s'agit généralement de tâches combinatoires, gourmandes en temps de calcul et en espace mémoire. Réaliser ces tâches intégralement en ligne dégrade la réactivité du système ; les réaliser intégralement hors ligne, en anticipant toutes les situations possibles, nuit à son embarquabilité. Les techniques de compilation de connaissances sont susceptibles d'apporter un compromis, en déportant au maximum l'effort de calcul avant la mise en situation du système. Ces techniques consistent à traduire un problème dans un certain langage, fournissant une forme compilée de ce problème, dont la résolution est facile et la taille aussi compacte que possible. La traduction peut être très longue, mais n'est effectuée qu'une seule fois, hors ligne. Il existe de nombreux langages-cible de compilation, notamment le langage des diagrammes de décision binaires (BDDs), qui ont été utilisés avec succès dans divers domaines (model-checking, configuration, planification). L'objectif de la thèse était d'étudier l'application de la compilation de connaissances à la conduite de systèmes autonomes. Nous nous sommes intéressés à des problèmes réels de planification, qui impliquent souvent des variables continues ou à grand domaine énuméré (temps ou mémoire par exemple). Nous avons orienté notre travail vers la recherche et l'étude de langages-cible de compilation assez expressifs pour permettre de représenter de tels problèmes.Controlling autonomous systems requires to make decisions depending on current observations and objectives. This involves some tasks that must be executed online-with the embedded computational power only. However, these tasks are generally combinatory; their computation is long and requires a lot of memory space. Entirely executing them online thus compromises the system's reactivity. But entirely executing them offline, by anticipating every possible situation, can lead to a result too large to be embedded. A tradeoff can be provided by knowledge compilation techniques, which shift as much as possible of the computational effort before the system's launching. These techniques consists in a translation of a problem into some language, obtaining a compiled form of the problem, which is both easy to solve and as compact as possible. The translation step can be very long, but it is only executed once, and offline. There are numerous target compilation languages, among which the language of binary decision diagrams (BDDs), which have been successfully used in various domains of artificial intelligence, such as model-checking, configuration, or planning. The objective of the thesis was to study how knowledge compilation could be applied to the control of autonomous systems. We focused on realistic planning problems, which often involve variables with continuous domains or large enumerated domains (such as time or memory space). We oriented our work towards the search for target compilation languages expressive enough to represent such problems

Diagnostic distribué de systèmes respectant la confidentialité

Dans cette thèse, nous nous intéressons à diagnostiquer des systèmes intrinsèquement distribués (comme les systèmes pairs-à-pairs) où chaque pair n'a accès qu'à une sous partie de la description d'un système global. De plus, en raison d'une politique d'accès trop restrictive, il sera pourra qu'aucun pair ne puisse expliquer le comportement du système global. Dans ce contexte, le challenge du diagnostic distribué est le suivant: expliquer le comportement global d'un système distribué par un ensemble de pairs ayant chacun une vision limitée, tout comme l'aurait fait un unique pair diagnostiqueur ayant, lui, une vision globale du système.D'un point de vue théorique, nous montrons que tout nouveau système, logiquement équivalent au système pair-à-pairs initialement observé, garantit que tout diagnostic local d'un pair pourra être prolongé par un diagnostic global (dans ce cas, le nouveau système est dit correct pour le diagnostic distribué).Nous montrons aussi que si ce nouveau système est structuré (c-à-d: il contient un arbre couvrant pour lequel tous les pairs contenant une même variable forme un graphe connecté) alors il garantit que tout diagnostic global pourra être retrouvé à travers un ensemble de diagnostics locaux des pairs (dans ce cas le nouveau système est dit complet pour le diagnostic distribué).Dans un souci de représentation succincte et afin de respecter la politique de confidentialité du vocabulaire de chacun des pairs, nous présentons un nouvel algorithme Token Elimination (TE), qui décompose le système de pairs initial vers un système structuré.Nous montrons expérimentalement que TE produit des décompositions de meilleurs qualité (c-à-d: de plus petites largeurs arborescentes) que les méthodes envisagées dans un contexte distribué. À partir du système structuré construit par TE, nous transformons chaque description locale en une Forme Normale Disjonctive (FND) globalement cohérente.Nous montrons que ce dernier système garantit effectivement un diagnostic distribué correct et complet. En plus, nous exhibons un algorithme capable de vérifier efficacement que tout diagnostic local fait partie d'un diagnostic minimal global, faisant du système structuré de FNDs un système compilé pour le diagnostic distribué.In this thesis, we focus on diagnosing inherently distributed systems such as peer-to-peer, where each peer has access to only a sub-part of the description of an overall system.In addition, due to a too restrictive access control policy, it can be possible that neither peer nor supervisor is able to explain the behaviour of the overall system.The goal of distributed diagnosis is to explain the behaviour of a distributed system by a set of peers (each having a limited local view) as a single diagnosis engine having a global view of the overall system.First, we show that any new system logically equivalent to the initially observed peer-to-peer setting ensures that all diagnosis of a peer may be extended to a global diagnosis (in this case the new system ensures correctness of the distributed diagnosis).Moreover, we prove that if the new system is structured (i.e.it contains a spanning tree for which all peers containing the same variable form a connected graph) then it ensures that any global diagnosis can be found through a set of local diagnoses (in this case the new system ensures the completeness of the distributed diagnoses).For a succinct representation and in order to comply with the privacy policy of the vocabulary of each peer, we present a new algorithm Token Elimination (TE), which decomposes the original peer system to a structured one.We experimentally show that TE produces better quality decompositions (i.e. smaller tree widths) than proposed methods in a distributed context.From the structured system built by TE, we transform each local description into globally consistent DNF.We demonstrate that the latter system is correct and complete for the distributed diagnosis.Finally, we present an algorithm that can effectively check that any local diagnosis is part of a global minimal diagnosis, turning the structured system of DNFs into a compiled system for distributed diagnosis.PARIS11-SCD-Bib. électronique (914719901) / SudocSudocFranceF