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53
Probabilistic Horn abduction and Bayesian networks
 Artificial Intelligence
, 1993
"... This paper presents a simple framework for Hornclause 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 Bayesia ..."
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Cited by 298 (37 self)
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This paper presents a simple framework for Hornclause 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 Bayesian belief network can be represented in this framework. The main contribution is in finding a relationship between logical and probabilistic notions of evidential reasoning. This provides a useful representation language in its own right, providing a compromise between heuristic and epistemic adequacy. It also shows how Bayesian networks can be extended beyond a propositional language. This paper also shows how a language with only (unconditionally) independent hypotheses can represent any probabilistic knowledge, and argues that it is better to invent new hypotheses to explain dependence rather than having to worry about dependence in the language. Scholar, Canadian Institute for Advanced...
The Complexity of LogicBased Abduction
, 1993
"... Abduction is an important form of nonmonotonic reasoning allowing one to find explanations for certain symptoms or manifestations. When the application domain is described by a logical theory, we speak about logicbased abduction. Candidates for abductive explanations are usually subjected to minima ..."
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Cited by 163 (26 self)
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Abduction is an important form of nonmonotonic reasoning allowing one to find explanations for certain symptoms or manifestations. When the application domain is described by a logical theory, we speak about logicbased abduction. Candidates for abductive explanations are usually subjected to minimality criteria such as subsetminimality, minimal cardinality, minimal weight, or minimality under prioritization of individual hypotheses. This paper presents a comprehensive complexity analysis of relevant decision and search problems related to abduction on propositional theories. Our results indicate that abduction is harder than deduction. In particular, we show that with the most basic forms of abduction the relevant decision problems are complete for complexity classes at the second level of the polynomial hierarchy, while the use of prioritization raises the complexity to the third level in certain cases.
Narratives in the Situation Calculus
, 1994
"... A narrative is a course of real events about which we might have incomplete information. Formalisms for reasoning about action may be broadly divided into those which are narrativebased, such as the Event Calculus of Kowalski and Sergot, and those which reason on the level of hypothetical sequences ..."
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Cited by 77 (5 self)
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A narrative is a course of real events about which we might have incomplete information. Formalisms for reasoning about action may be broadly divided into those which are narrativebased, such as the Event Calculus of Kowalski and Sergot, and those which reason on the level of hypothetical sequences of actions, in particular the Situation Calculus. This paper bridges the gap between these types of formalism by supplying a technique for linking incomplete narrative descriptions to Situation Calculus domain formulae written in the usual style using a Result function. Particular attention is given to actions with duration and overlapping actions. By illuminating the relationship between these two different styles of representation, the paper moves us one step closer to a full understanding of the space of all possible formalisms for reasoning about action. Introduction The Situation Calculus [15] is one of A.I.'s oldest and best understood formalisms for representing change, but it has of...
The Diagnosis Frontend of the dlv System
 AI Communications
, 1999
"... This paper presents the Diagnosis Frontend of dlv, which is a knowledge representation system under development at the Technische Universität Wien. The kernel language of the system is an extension of disjunctive logic programming (DLP) by integrity constraints; it offers frontends to several advanc ..."
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Cited by 45 (7 self)
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This paper presents the Diagnosis Frontend of dlv, which is a knowledge representation system under development at the Technische Universität Wien. The kernel language of the system is an extension of disjunctive logic programming (DLP) by integrity constraints; it offers frontends to several advanced knowledge representation formalisms. The formal model of diagnosis employed in the frontend includes both abductive diagnosis (over DLP theories) and consistencybased diagnosis. For each of the two diagnosis modalities, generic diagnoses, single error diagnoses, and subset minimal diagnoses are considered. We illustrate the use of the frontend by showing the dlv encodings of several diagnosis problems. Thereafter, we discuss implementation issues. Diagnostic reasoning is implemented on the dlv engine through suitable translations of diagnostic problems into disjunctive logic programs, such that their stable models correspond to diagnoses. For the six kinds of diagnostic reasoning problems emerging from above, such reductions are provided
A Fixpoint Characterization Of Abductive Logic Programs
, 1996
"... this paper, we generalize the program transformation techniques of [17] for nonabductive programs to deal with abductive frameworks. We introduce a new translation from an abductive logic program into a positive disjunctive program, and show that the belief models of an abductive program can be cha ..."
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Cited by 38 (8 self)
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this paper, we generalize the program transformation techniques of [17] for nonabductive programs to deal with abductive frameworks. We introduce a new translation from an abductive logic program into a positive disjunctive program, and show that the belief models of an abductive program can be characterized by the fixpoint closure of the transformed disjunctive program. In the transformation, both negative hypotheses through negation as failure and positive hypotheses from the abducibles are dealt with uniformly. This fixpoint characterization is further extended to a fixpoint semantics for abductive extended disjunctive programs, i.e., abductive programs that permit classical negation as well as disjunctions. For a procedural aspect of our fixpoint semantics, we also show that a model generation procedure for positive disjunctive programs can be used as a sound and complete procedure for computing belief models for functionfree and rangerestricted programs.
Abduction from Logic Programs: Semantics and Complexity
 Theoretical Computer Science
, 1998
"... Abduction from observations and a theory, find using hypotheses an explanation for the observations  gained increasing interest during the last years. This form of reasoning has wide applicability in different areas of computer science; in particular, it has been recognized as an important pr ..."
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Cited by 37 (7 self)
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Abduction from observations and a theory, find using hypotheses an explanation for the observations  gained increasing interest during the last years. This form of reasoning has wide applicability in different areas of computer science; in particular, it has been recognized as an important principle of commonsense reasoning. In this paper, we define a general abduction model for logic programming, where the inference operator (i.e., the semantics to be applied on programs), can be specified by the user. Advanced forms of logic programming have been proposed as valuable tools for knowledge representation and reasoning. We show that logic programming semantics can be more meaningful for abductive reasoning than classical inference by providing examples from the area of knowledge representation and reasoning. The main part of the paper is devoted to an extensive study of the computational complexity of the principal problems in abductive reasoning, which are: Given an inst...
Enhancing Model Checking in Verification by AI Techniques
 Artificial Intelligence
, 1999
"... Model checking is a fruitful application of computational logic with high relevance to the verification of concurrent systems. While model checking is capable of automatically testing that a concurrent system satisfies its formal specification, it can not precisely locate an error and suggest a r ..."
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Cited by 22 (2 self)
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Model checking is a fruitful application of computational logic with high relevance to the verification of concurrent systems. While model checking is capable of automatically testing that a concurrent system satisfies its formal specification, it can not precisely locate an error and suggest a repair, i.e., a suitable correction, to the system. In this paper, we tackle this problem by using principles from AI. In particular, we introduce the abstract concept of a system repair problem, and exemplify this concept on repair of concurrent programs and protocols. For the development of our framework, we formally extend the concept of counterexample, which has been proposed in model checking previously, and provide examples which demonstrate the need for such an extension. Moreover, we investigate into optimization issues for the problem of finding a repair, and present techniques which gain in some cases a considerable reduction of the search space for a repair.
Semantics and complexity of abduction from default theories
 Artificial Intelligence
, 1997
"... Since logical knowledge representation is commonly based on nonclassical formalisms like default logic, autoepistemic logic, or circumscription, it is necessary to perform abductive reasoning from theories of nonclassical logics. In this paper, we investigate how abduction can be performed from theo ..."
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Cited by 21 (2 self)
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Since logical knowledge representation is commonly based on nonclassical formalisms like default logic, autoepistemic logic, or circumscription, it is necessary to perform abductive reasoning from theories of nonclassical logics. In this paper, we investigate how abduction can be performed from theories in default logic. Different modes of abduction are plausible, based on credulous and skeptical default reasoning; they appear useful for different applications such as diagnosis and planning. Moreover, we analyze the complexity of the main abductive reasoning tasks. They are intractable in the general case; we also present known classes of default theories for which abduction is tractable. 1
Abduction in Logic Programming: A New Definition and an Abductive Procedure Based on Rewriting
 Artificial Intelligence
, 2002
"... We propose a new definition of abduction in logic programming, and contrast it with that of Kakas and Mancarella's. We then introduce a rewriting system for answering queries and generating explanations, and show that it is both sound and complete under the partial stable model semantics and so ..."
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Cited by 20 (5 self)
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We propose a new definition of abduction in logic programming, and contrast it with that of Kakas and Mancarella's. We then introduce a rewriting system for answering queries and generating explanations, and show that it is both sound and complete under the partial stable model semantics and sound and complete under the answer set semantics when the underlying program is socalled oddloop free. We discuss an application of the work to a problem in reasoning about actions and provide some experimental results. 1 Abduction in logic programming In general, given a background theory T , and an observation q to explain, an abduction of q w.r.t. T is a theory \Pi such that \Pi [ T j= q. Normally, we want to put some additional conditions on \Pi, such as that it is consistent with T and contains only those propositions called abducibles. For instance, in propositional logic, given a background theory T , a set A of assumptions or abducibles, and a proposition q, an explanation S...