This paper presents a simple framework for Horn-clause abduction, with probabilities associated with hypotheses. The framework incorporates assumptions about the rule base and independence assumptions amongst hypotheses. It is shown how any probabilistic knowledge representable in a discrete

In this paper we (1) define the concept of a Clause Man-agetnent System (CMS) — a generaizatiou of de Kleer’s ATMS, (2) motivate such systems in terms of efficiency of search and abductive reasoning, and (3) characterize the computation affected by a CMS in terms of the concept of prime implicants

Paul Bourgine's text "Models of Abduction " is undoubtfully ingenious, bringing forth a theory of abduction whose purpose is to check its adequacy for the whole field of cognitive science. I will not face Bourgine's text directly and I have sincerely to confess

Abduction is a form of non-monotonic reasoning that has gained increasing interest in the last few years. The key idea behind it can be represented by the following inference rule $$O = \mathop C\limits_| - N = \mathop P\limits_|^| - O - \mathop C\limits_|^| - .$$ i.e., from an occurrence of ohgr

abduction and logic programming is at two levels. At the first level probabilistic Horn abduction is an extension of pure Prolog, that is useful for diagnosis and other evidential reasoning tasks. At another level, current logic programming implementation techniques can be used to efficiently implement

. An abductive framework is described for validating theories using a library of known or desired behaviour. Abduction is known to be NP-hard which suggests that this framework is impractical for anything other than small theories. The computational limits of the framework is therefore explored. We

Abstract We present an experiment for evaluating precise and imprecise evidential combination operators. The experiment design is based on the assumption that only limited statistical information is available in the form of multinomial observations. We evaluate three different evidential

of the existing Shafer-Dempster theory is limited by the lack of an effective approach for dealing with beliefs about continuous variables. This paper introduces a uew representation of belief for continuous variables that provides both a conceptual framework and a computation-ally tractable implementation within

individuals (things). This paper shows how decision theory and logical argumentation can be combined into a coherent framework. The Independent Choice Logic can be viewed as first-order representation of belief networks with conditional probability tables represented as first-order rules, or as a abductive

with complexity results on the generation of abductive explanations. By syntactically restricting the description of our theory of system behavior or by limiting the completeness of our abductive reasoning, we are able to gain insight into tractable test generation problems. 1 INTRODUCTION Diagnostic