Characterizing diagnoses and systems (original) (raw)
Related papers
Lecture Notes in Computer Science, 1990
Most approaches to model-based diagnosis describe a diagnosis for a system as a set of failing components that explains the symptoms. In order to characterize the typically very large number of diagnoses, usually only the minimal such sets of failing components are represented. This method of characterizing all diagnoses is inadequate in general, in part because not every superset of the faulty components of a diagnosis necessarily provides a diagnosis. In this paper we analyze the notion of diagnosis in depth exploiting the notions of implicate/implicant and prime implicate/implicant. We use these notions to propose two alternative approaches for addressing the inadequacy of the concept of minimal diagnosis. First, we propose a new concept, that of kernel diagnosis, which is free of the problems of minimal diagnosis. Second, we propose to restrict the axioms used to describe the system to ensure that the concept of minimal diagnosis is adequate.
Normality and faults in logic-based diagnosis
1989
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.
SOME CONCEPT OF DIAGNOSTIC REASONING FOR SYSTEMS WITH UNCERTINTY
Scientific Bulletin Series C - Fascicle Mechanics, Tribology, Machine Manufacturing Technology, 2003
The diagnostic reasoning for systems with uncertainty is the main difficulty in modern diagnostic. Uncertainty is present in the most of diagnosed systems รข?? from medicine to technical applications. Usage of different methods in tasks of diagnostic reasoning connected with these problems has been presented. A wide range of conclusions associated with diagnostic systems creating can be used by designers of these systems.
2013
The existing theory of consistency-based diagnosis and its implementations have proven successful in a number of technical applications. However, they turn out to be inherently limited to a very specific class of systems to be diagnosed: They are tailored for artifacts consisting of components in a fixed structure, and they are aimed at a particular kind of diagnosis and repair, namely failing components and their replacement. In order to cover systems that comprise processes and change their structure dynamically, faults that are due to unanticipated objects and interactions, and therapy tasks that involve complex interference with the system, we need an extended theory of diagnosis and therapy. In this paper, we present theoretical and practical results of our work on process-oriented consistency-based diagnosis. For this purpose, a logical reconstruction of a processoriented modeling paradigm is needed, which forms the foundation for both the automated composition and the revisio...
Declarative Diagnosis Revisited
1995
We extend the declarative diagnosis methods to the diagnosis w.r.t. computed answers. We show that absence of uncovered atoms implies completeness for a large class of programs. We then define a top-down diagnoser, which uses one oracle only, does not require to determine in advance the symptoms and is driven by a (finite) set of goals. Finally we tackle the problem of effectivity, by introducing (finite) partial specifications. We obtain an effective diagnosis method, which is weaker than the general one in the case of correctness, yet can efficiently be implemented in both a top-down and in a bottom-up style.
On the efficiency of logic-based diagnosis
Proceedings of the third international conference on Industrial and engineering applications of artificial intelligence and expert systems - IEA/AIE '90, 1990
Diagnosis is a problem in which one must explain the discrepancy between the observed and correct system behavior by assuming some component (possibly multiple components) of the system is functioning abnormally. A diagnostic reasoning system must deal with two issues concerning computational efficiency. The first is efficient search in a complex space for all possible diagnoses for a given set of observations about the faulty system. The second is efficient discrimination amongst multiple competing diagnoses. We consider the problem of diagnosis from the perspective of the Theorist hypothetical reasoning framework which provides a simple and intuitive diagnostic method. We propose an extension to the Theorist framework that modifies the consistency check mechanism to incrementally compute inconsisfencies, sometimes referred to as nogoods, and to identify crucial liter& to perform tests for discriminating among competing diagnoses. A prototype is implimented in Cprolog and its empirical efficiency is shown by considering examples from two different domains of diagnosis. 1 Introduction Diagnosis is a problem in which one must explain discrepancies between observed and correct system behavior. Because of the ubiquity of this problem in real world situations, including failure of a nuclear plant, medical diagnosis, faults in an electronic circuit, etc., Permission to copy without fee all or part of this material is granted provided that the copies are not made or distributed for direct commercial advantage, the ACM copyright notice and the title of the publication and its date appear, and notice is given that copying is by permission of the Association for Computing Machinery. To copy otherwise, or to republish, requires a fee and/or specific permission.
A formal model of diagnostic inference. I. Problem formulation and decomposition
Information Sciences, 1985
This paper, which is Part I of a two-part series, introduces a new model of diagnostic problem solving based on a generalization of the set-covering problem. The model formalizes the concepts of (1) whether or not a set of one or more disorders is sufficient to explain a set of occurring manifestations,(2) what a solution is for a diagnostic problem, and(3) how to generate all of the alternative explanations in a problem's solution.
Abstract:-Reasoning about real-world problems is only possible if assumptions are made. Assumptions can be formulated as constraints or requirements that must be satisfied. The aim of introducing assumption, whether implicit or explicit, is usually to circumscribe the domain and/or to restrict the complexity of the problem. In this paper, we present a three-valued nonmonotonic logic system L3 that is naturally suitable for diagnostic reasoning and allows us to represent and reason about assumptions employed in approaches to ...
Explanatory diagnoses and their characterization by circumscription
Annals of Mathematics and Artificial Intelligence, 1994
Making a diagnosis amounts to determining what is the state of each component in a given system on the basis of a set of observations from the behaviour of that system. In the "model-based" approach to diagnosis, a diagnosis relies on a (possibly incomplete) description of the expected behaviour of the system. A diagnosis thus consists of the state of the components of the system and has to be consistent with the description (i.e. the model) of the system and the observations that are made. Yet, it is not enough, and additional criteria are needed to select some diagnoses that are more likely to coincide with the true state of the system. The criteria which are most often quoted in the literature are minimality, parsimony, exoneration, explainability. Non-monotonic logics are well suited to express such preferences formally. Indeed, Reiter shows how the minimality criterion can be formalized in default logic; Console, Dupr6 and Torasso employ predicate completion to model an abductive approach to diagnosis; Raiman resorts to circumscription as a means to exonerate the components exhibiting a normal behaviour. In this paper, we focus on an abduction-based explainability approach to diagnosis, through a formalization in terms of circumscription. The approach that we develop here deals with deductiveabductive diagnoses which explain the observations "as far as possible". For this reason we call them explanatory diagnoses. After an introductory section, we first define explanatory diagnoses precisely. Next, we show how circumscription can be used to give a formal characterization of explanatory diagnoses and illustrate it with an example. We stress that, with this approach, no completeness condition is imposed on the description of the system which can consist of fault models and/or models of correct behaviour.