The AI literature contains many definitions of diagnostic reasoning most of which are defined in terms of the logical entailment relation. We use existing work on approximate entailment to define notions of approximation in diagnosis. We show how such a notion of approximate diagnosis can be exploited in various diagnostic strategies. We illustrate these strategies by performing diagnosis in a small car domain example
. The aim of this paper is to present an approach to the integration of Case-Based Reasoning with Mo...
Abstract. Approximate reasoning for the Semantic Web is based on the idea of sacrificing soundness o...
Model-based diagnosis (MBD) provides several advantages over experiential rule-based systems. A prin...
The most widely accepted models of diagnostic reasoning are all phrased in terms of the logical cons...
The most widely accepted models of diagnostic reasoning are all phrased in terms of the logical cons...
We argue that diagnosis should not be seen as solving a problem with a unique definition, but rather...
The use of approximation as a method for dealing with com-plex problems is a fundamental research is...
AbstractThe idea of approximate entailment has been proposed by Schaerf and Cadoli [Tractable reason...
AbstractThe idea of approximate entailment has been in [13] as a way of modeling the reasoning of an...
AbstractProblems in logic are well known to be hard to solve in the worst case. Two different strate...
We propose to extend the ontology of logical AI to include approximate objects, approximate predicat...
Abstract. This paper introduces some preliminary formalizations of the approximate entities of [McCa...
Approximation techniques are widely used in many areas of Computer Science for dealing with polynomi...
Abstract. Real agents (natural or artificial) are limited in their reasoning capabilities. In this p...
Many AI problems, when formulated, reduce to evaluating the probability that a prepositional express...
. The aim of this paper is to present an approach to the integration of Case-Based Reasoning with Mo...
Abstract. Approximate reasoning for the Semantic Web is based on the idea of sacrificing soundness o...
Model-based diagnosis (MBD) provides several advantages over experiential rule-based systems. A prin...
The most widely accepted models of diagnostic reasoning are all phrased in terms of the logical cons...
The most widely accepted models of diagnostic reasoning are all phrased in terms of the logical cons...
We argue that diagnosis should not be seen as solving a problem with a unique definition, but rather...
The use of approximation as a method for dealing with com-plex problems is a fundamental research is...
AbstractThe idea of approximate entailment has been proposed by Schaerf and Cadoli [Tractable reason...
AbstractThe idea of approximate entailment has been in [13] as a way of modeling the reasoning of an...
AbstractProblems in logic are well known to be hard to solve in the worst case. Two different strate...
We propose to extend the ontology of logical AI to include approximate objects, approximate predicat...
Abstract. This paper introduces some preliminary formalizations of the approximate entities of [McCa...
Approximation techniques are widely used in many areas of Computer Science for dealing with polynomi...
Abstract. Real agents (natural or artificial) are limited in their reasoning capabilities. In this p...
Many AI problems, when formulated, reduce to evaluating the probability that a prepositional express...
. The aim of this paper is to present an approach to the integration of Case-Based Reasoning with Mo...
Abstract. Approximate reasoning for the Semantic Web is based on the idea of sacrificing soundness o...
Model-based diagnosis (MBD) provides several advantages over experiential rule-based systems. A prin...