Abstract Machine learning promises to revolutionize clinical decision making and diagnosis.
In medical diagnosis a doctor aims to explain a patient's symptoms by determining the …

In an increasingly competitive marketplace system complexity continues to grow, but time-to-
market and lifecycle are reducing. The purpose of fault diagnosis is the isolation of faults on …

Diagnostic tasks require determining the differences between a model of an artifact and the
artifact itself. The differences between the manifested behavior of the artifact and the …

Constraint sets can become inconsistent in different contexts. For example, during a
configuration session the set of customer requirements can become inconsistent with the …

Abstract Argumentation is a promising approach to handle inconsistent knowledge bases,
based on the justification of plausible conclusions by arguments. Because of inconsistency …

This paper presents a methodology for extending representation and reasoning in
Qualitative Physics. This methodology is presently used for various applications. The …

This paper presents and discusses several methods for reasoning from inconsistent
knowledge bases. A so-called argued consequence relation, taking into account the …

Abstract Model-based diagnosis is based on first-principles reasoning using the behavioral
specifications of the primitive components of a device. Unless the computational architecture …

This book is about model-based diagnosis of a class of discrete-event systems called active
systems. Roughly, model-based diagnosis is the task of finding out the faulty components of …

This paper investigates several methods for coping with inconsistency caused by multiple
source information, by introducing suitable consequence relations capable of inferring non …