Normality and faults in logic-based diagnosis
Published 20 August 1989
David Poole
Citations155
Generate an AI Snapshot to get a quick, structured summary of this paper.
Study Snapshot
ObjectiveStudy objective
MethodsResearch methodology
PopulationPopulation studied
Sample sizeSample sizes
OutcomesStudy outcomes here
ResultsStudy results comes here
LimitationsResearch study limitations comes here
A concise AI-generated summary of the paper will appear here once you click Generate AI Snapshot.
Abstract
Is there one logical definition of diagnosis? In this paper I argue that the answer to this question is "no". This paper is about the pragmatics of using logic for diagnosis; we show how two popular proposals for using logic for diagnosis, (namely abductive and consistency-based approaches) can be used to solve diagnostic tasks. The cases with only knowledge about how normal components work (any deviation being an error) and where there are fault models (we try to find a covering of the observations) are considered as well as the continuum between. The result is that there are two fundamentally different, but equally powerful diagnostic paradigms. They require different knowledge about the world, and different ways to think about a domain. This result indicates that there may not be an axiomatisation of a domain that is independent of how the knowledge is to be used.
Keywords
Computer Science
Elsevier eBooksSome Philosophical Problems from the Standpoint of Artificial Intelligence
3,289 Citations1981John McCarthy, Patrick J. Hayes
The formalism of this paper represents an advance over McCarthy (1963) and Green (1969) in that it permits proof of the correctness of strategies that contain loops and strategies that involve the acquisition of knowledge; and it is also somewhat more concise.
Artificial IntelligenceA theory of diagnosis from first principles
2,897 Citations1987Raymond Reiter
The theory accommodates diagnostic reasoning in a wide variety of practical settings, including digital and analogue circuits, medicine, and database updates, and reveals close connections between diagnostic reasoning and nonmonotonic reasoning.
Artificial IntelligenceDiagnosing multiple faults
2,053 Citations1987Johan de Kleer, Brian C. Williams
The diagnostic procedure presented in this paper is model-based, inferring the behavior of the composite device from knowledge of the structure and function of the individual components comprising the device.
Artificial IntelligenceA logical framework for default reasoning
723 Citations1988David Poole
A simple logical framework for default reasoning by treating defaults as predefined possible hypotheses is presented, and it is shown how this idea subsumes the intuition behind Reiter's default logic.
Communications of the ACMAlgorithm = logic + control
602 Citations1979Robert Kowalski
The notion that computation = controlled deduction was first proposed by Pay Hayes and more recently by Bibel and Vaughn-Pratt and the thesis that algorithms be regarded as consisting of both logic and control components is explored.
Artificial IntelligenceThe use of design descriptions in automated diagnosis
537 Citations1984Michael Genesereth
Dart differs from previous approaches to diagnosis taken in the design-automation community in that it is more general and in many cases more efficient, and allows it to be applied to a wide class of devices ranging from digital logic to nuclear reactors.
International Journal of Man-Machine StudiesDiagnostic expert systems based on a set covering model
393 Citations1983James A. Reggia, Dana Nau +1 more
It is proposed that a generalization of the set covering problem can be used as an intuitively plausible model for diagnostic problem solving and potentially useful as a basis for expert systems in that it provides a solution to the difficult problem of multiple simultaneous disorders.
Theorist: A Logical Reasoning System for Defaults and Diagnosis
308 Citations1987David Poole, Randy Goebel +1 more
This work provides an introduction to Theorist, a logic programming system that uses a uniform deductive reasoning mechanism to construct explanations of observations in terms of facts and hypotheses.
Computational IntelligenceExplanation and prediction: an architecture for default and abductive reasoning
212 Citations1989David Poole
This paper elaborates on the idea that reasoning should be viewed as theory formation where logic tells us the consequences of the authors' assumptions, and proposes an architecture to combine explanation and prediction into one coherent framework.
Representing Knowledge for Logic-Based Diagnosis.
73 Citations1988David Poole
There seems as though there is no one framework which can claim to be the logical de nition of diagnosis, so this paper concentrates on the case where the authors have fault models.
SLPGeneral Diagnosis by Abductive Inference.
60 Citations1987Philip T. Cox, Tomasz Pietrzykowski
Results provide strong evidence that antigen recognition by H-2-restricted CTL is not mediated by two independent antigen receptors.
International Journal of Approximate ReasoningTowards solving the multiple extension problem: Combining defaults and probabilities
14 Citations1988
This work suggests a framework that combines probabilities and defaults in a single unified framework that retains the semantics of diagnosis as construction of explanations from a fixed set of possible hypotheses that can then compute probabilities incrementally as the authors construct explanations.