Results 1  10
of
23
A Theory of Diagnosis from First Principles
 ARTIFICIAL INTELLIGENCE
, 1987
"... Suppose one is given a description of a system, together with an observation of the system's behaviour which conflicts with the way the system is meant to behave. The diagnostic problem is to determine those components of the system which, when assumed to be functioning abnormally, will explain ..."
Abstract

Cited by 1060 (5 self)
 Add to MetaCart
Suppose one is given a description of a system, together with an observation of the system's behaviour which conflicts with the way the system is meant to behave. The diagnostic problem is to determine those components of the system which, when assumed to be functioning abnormally, will explain the discrepancy between the observed and correct system behaviour. We propose a general theory for this problem. The theory requires only that the system be described in a suitable logic. Moreover, there are many such suitable logics, e.g. firstorder, temporal, dynamic, etc. As a result, the theory accommodates diagnostic reasoning in a wide variety of practical settings, including digital and analogue circuits, medicine, and database updates. The theory leads to an algorithm for computing all diagnoses, and to various results concerning principles of measurement for discriminating among competing diagnoses. Finally, the theory reveals close connections between diagnostic reasoning and nonmonotonic reasoning.
Hierarchical ModelBased Diagnosis
 International Journal of ManMachine Studies
, 1991
"... Modelbased reasoning about a system requires an explicit representation of the system's components and their connections. Diagnosing such a system consists of locating those components whose abnormal behavior accounts for the faulty system behavior. In order to increase the efficiency of model ..."
Abstract

Cited by 35 (2 self)
 Add to MetaCart
Modelbased reasoning about a system requires an explicit representation of the system's components and their connections. Diagnosing such a system consists of locating those components whose abnormal behavior accounts for the faulty system behavior. In order to increase the efficiency of modelbased diagnosis, we propose a model representation at several levels of detail, and define three refinement (abstraction) operators. We specify formal conditions that have to be satisfied by the hierarchical representation, and emphasize that the multilevel scheme is independent of any particular singlelevel model representation. The hierarchical diagnostic algorithm which we define turns out to be very general. We show that it emulates the bisection method, and can be used for hierarchical constraint satisfaction. We apply the hierarchical modeling principle and diagnostic algorithm to a mediumscale medical problem. The performance of a fourlevel qualitative model of the heart is compared t...
Symbolic Diagnosis and its Formalisation
 The Knowledge Engineering Review
, 1997
"... Diagnosis was among the first subjects investigated when digital computers became available. It still remains an important research area, in which several new developments have taken place in the last decade. One of these new developments is the use of detailed domain models in knowledgebased syste ..."
Abstract

Cited by 32 (6 self)
 Add to MetaCart
Diagnosis was among the first subjects investigated when digital computers became available. It still remains an important research area, in which several new developments have taken place in the last decade. One of these new developments is the use of detailed domain models in knowledgebased systems for the purpose of diagnosis, often referred to as modelbased diagnosis. Typically, such models embody knowledge of the normal or abnormal structure and behaviour of the modelled objects in a domain. Models of the structure and workings of technical devices, and causal models of disease processes in medicine are two examples. In this article, the most important notions of diagnosis and their formalisation are reviewed and brought in perspective. In addition, attention is focused on a number of general frameworks of diagnosis, which offer sufficient flexibility for expressing several types of diagnosis.
Analysis of Notions of Diagnosis
, 1998
"... Various formal theories have been proposed in the literature to capture the notions of diagnosis underlying diagnostic programs. Examples of such notions are: heuristic classification, which is used in systems incorporating empirical knowledge, and modelbased diagnosis, which is used in diagnostic ..."
Abstract

Cited by 23 (2 self)
 Add to MetaCart
Various formal theories have been proposed in the literature to capture the notions of diagnosis underlying diagnostic programs. Examples of such notions are: heuristic classification, which is used in systems incorporating empirical knowledge, and modelbased diagnosis, which is used in diagnostic systems based on detailed domain models. Typically, such domain models include knowledge of causal, structural, and functional interactions among modelled objects. In this paper, a new settheoretical framework for the analysis of diagnosis is presented. Basically, the framework distinguishes between `evidence functions', which characterize the net impact of knowledge bases for purposes of diagnosis, and `notions of diagnosis', which define how evidence functions are to be used to map findings observed for a problem case to diagnostic solutions. This settheoretical framework offers a simple, yet powerful tool for comparing existing notions of diagnosis, as well as for proposing new notions ...
Modelbased diagnostics and probabilistic assumptionbased reasoning
 Artificial Intelligence
, 1998
"... The mathematical foundations of modelbased diagnostics or diagnosis from first principles have been laid by Reiter [31]. In this paper we extend Reiter’s ideas of modelbased diagnostics by introducing probabilities into Reiter’s framework. This is done in a mathematically sound and precise way whi ..."
Abstract

Cited by 23 (17 self)
 Add to MetaCart
(Show Context)
The mathematical foundations of modelbased diagnostics or diagnosis from first principles have been laid by Reiter [31]. In this paper we extend Reiter’s ideas of modelbased diagnostics by introducing probabilities into Reiter’s framework. This is done in a mathematically sound and precise way which allows one to compute the posterior probability that a certain component is not working correctly given some observations of the system. A straightforward computation of these probabilities is not efficient and in this paper we propose a new method to solve this problem. Our method is logicbased and borrows ideas from assumptionbased reasoning and ATMS. We show how it is possible to determine arguments in favor of the hypothesis that a certain group of components is not working correctly. These arguments represent the symbolic or qualitative aspect of the diagnosis process. Then they are used to derive a quantitative or numerical aspect represented by the posterior probabilities. Using two new theorems about the relation between Reiter’s notion of conflict and our notion of argument, we prove that our socalled degree of support is nothing but the posterior probability that we are looking for. Furthermore, a model where each component may have more than two different operating modes is discussed and a new algorithm to compute posterior probabilities in this case is presented. Key words: Modelbased diagnostics; Assumptionbased reasoning; ATMS;
Diagnosis based on description of structure and function
 In Second National Conference on Artificial Intelligence, 1982 (AAAI
, 1982
"... While expert systems have traditionally been built using large coliections of rules based on empirlcal associations, interest has grown recently in the use of systems that reason from representations of structure and function. Our work explores the use of such models in troubleshooting digital elect ..."
Abstract

Cited by 21 (3 self)
 Add to MetaCart
(Show Context)
While expert systems have traditionally been built using large coliections of rules based on empirlcal associations, interest has grown recently in the use of systems that reason from representations of structure and function. Our work explores the use of such models in troubleshooting digital electronics. We describe our work to date on (i) a language for describing structure, (ii) a language for describing function, and (i/i) a set of prlnctples for troubleshooting that uses the two descriptions to guide its investigation. In discussing troubleshooting we show why the traditional approach test generation solves a different [JrdJklll dnti vve &SCllSS a Ilumber of its pIdC,hd ShOrt~Olllill~S. We consider next the style of debugging known as violated expectations and demonstrate why it is a fundclmental advance over traditional test generation. Further exploration of this approach. however, demonstrates that it is incapable of dealing with commonly known classes of faults. We explain the shortcoming as arisirlg from the use of a fault model that is both implicit and inseparable from the basic troubleshooting metl~odology. We argue for the importance of fault models that are explicit, separated from the troubleshooting mechanism, and retractable in much the same sense that inferences are retracted in current systems.
Bayesian Modelbased Diagnosis
 International Journal of Approximate Reasoning
, 2001
"... Modelbased diagnosis concerns using a model of the structure and behaviour of a system or device in order to establish why the system or device is malfunctioning. Traditionally, little attention has been given to the problem of dealing with uncertainty in modelbased diagnosis. Given the fact th ..."
Abstract

Cited by 11 (2 self)
 Add to MetaCart
(Show Context)
Modelbased diagnosis concerns using a model of the structure and behaviour of a system or device in order to establish why the system or device is malfunctioning. Traditionally, little attention has been given to the problem of dealing with uncertainty in modelbased diagnosis. Given the fact that determining a diagnosis for a problem almost always involves uncertainty, this situation is not entirely satisfactory. This paper builds upon and extends previous work in modelbased diagnosis by supplementing the wellknown modelbased framework with mathematically sound ways for dealing with uncertainty.
The Art of the Propagator
, 2008
"... We develop a programming model built on the idea that the basic computational elements are autonomous machines interconnected by shared cells through which they communicate. Each machine continuously examines the cells it is interested in, and adds information to some based on deductions it can make ..."
Abstract

Cited by 9 (2 self)
 Add to MetaCart
(Show Context)
We develop a programming model built on the idea that the basic computational elements are autonomous machines interconnected by shared cells through which they communicate. Each machine continuously examines the cells it is interested in, and adds information to some based on deductions it can make from information from the others. This model makes it easy to smoothly combine expressionoriented and constraintbased programming; it also easily accommodates implicit incremental distributed search in ordinary programs.
Ordered Diagnosis
, 2003
"... We propose to regard a diagnostic system as an ordered logic theory, i.e. a partially ordered set of clauses where smaller rules carry more preference. ..."
Abstract

Cited by 7 (6 self)
 Add to MetaCart
We propose to regard a diagnostic system as an ordered logic theory, i.e. a partially ordered set of clauses where smaller rules carry more preference.
ModelBased Reliability and Diagnostic: A Common Framework for Reliability and Diagnostics
 DX’02 THIRTEENTH INTERNATIONAL WORKSHOP ON PRINCIPLES OF DIAGNOSIS
, 2002
"... Technical systems are in general not guaranteed to work correctly. They are more or less reliable. One main problem for technical systems is the computation of the reliability of a system. A second main problem is the problem of diagnostic. In fact, these problems are in some sense dual to each othe ..."
Abstract

Cited by 7 (2 self)
 Add to MetaCart
Technical systems are in general not guaranteed to work correctly. They are more or less reliable. One main problem for technical systems is the computation of the reliability of a system. A second main problem is the problem of diagnostic. In fact, these problems are in some sense dual to each other. In this