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Natural Language Processing

Abduction, that ubiquitous form of reasoning

Profile image of Ramón PineroRamón Pinero

1998, Expert Systems with Applications

Abstract

In recent years, attention has been devoted to abduction, a hypothetical form of non-monotonic reasoning that tries to fit the best 'explanation' to a given observation. In this paper we present a collection of applications of automated abductive reasoning developed in the Center for Artificial Intelligence of the ITESM (Monterrey, Mexico) in the last five years, covering a range from natural language understanding to software re-use.

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Pre-Proceedings of the 2007 International Workshop on Abduction and Induction in Artificial Intelligence (AIAI’07)
andrei doncescu

2007

Abduction and induction are forms of logical reasoning that are used in many applications of Artificial Intelligence (AI). Individually, abduction reasons from effects to possible causes, while induction learns general rules for particular observations. In combination, abduction and induction can be integrated within an iterative cycle of knowledge development.

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The Role of Abduction in Logic Programming
Antonis Kakas

Handbook of Logic in Artificial Intelligence and Logic Programming: Volume 5: Logic Programming, 1998

This paper extends and updates our earlier survey and analysis of work on the extension of logic programming to perform abductive reasoning [Kakas et al., 1993]. The purpose of the paper is to provide a critical overview of some of the main research results, in order to develop a common framework for evaluating these results, to identify the main unresolved problems, and to indicate directions for future work. The emphasis is not on technical details but on relationships and common features of different approaches. Some of the main issues we will consider are the contributions that abduction can make to the problems of reasoning with incomplete or negative information, the evolution of knowledge, and the semantics of logic programming and its extensions. We also discuss recent work on the argumentation-theoretic interpretation of abduction, which was introduced in the earlier version of this paper. The philosopher Peirce first introduced the notion of abduction. In [Peirce, 1931-58]...

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On the Relationship Between Abduction and Deduction
Daniele Theseider Dupre

Journal of Logic and Computation, 1991

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Abductive Reasoning: Challenges Ahead
Atocha Aliseda

THEORIA. An International Journal for Theory, History …, 2009

The purpose of this piece is to provide a critical analysis on some key aspects of abduction, as conceived by several researchers through my book Abductive Reasoning. These contributions raise fundamental questions concerning the conjectural character of ...

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An Overview of Abduction as a General Framework for Knowledge-Based Systems
Tim Menzies

1995

Abstract A single inference procedure (abduction) can be used for (amongst other things) prediction, classication, explanation. planning, monitoring, diagnosis, qualitative reasoning, validation, veri cation, diagrammatic reasoning, multiple-expert knowledge acquisition and decision support systems.

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Abductive Logic Programming
Bob Kowalski

Journal of Logic and Computation, 1992

This paper is a survey and critical overview of recent w ork on the extension of Logic Programming to perform Abductive Reasoning (Abductive Logic Programming). It updates the earlier paper \Abductive Logic Programming" 88]. We outline the general framework of Abduction and its applications to Knowledge Assimilation and Default Reasoning we describe the argumentation-theoretic approach to the use of abduction as an interpretation for Negation as Failure, introduced in the earlier version 88] of this paper and we present recent w ork on the generalisation of the argumentation-theoretic approach t o provide a framework for default reasoning in general. We also analyse the links between Abduction and Constraint Logic Programming, as well as between Abduction and the extension of Logic Programming obtained by adding a form of explicit negation. Finally we discuss the relation between Abduction and Truth Maintenance.

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Abductive reasoning through filtering
Chitta Baral

2000

Abduction is an inference mechanism where given a knowledge base and some observations, the reasoner tries to find hypotheses which together with the knowledge base explain the observations. A reasoning based on such an inference mechanism is referred to as abductive reasoning. Given a theory and some observations, by filtering the theory with the observations, we mean selecting only those models of the theory that entail the observations.

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Abduction in machine learning
Hector Alberto Delgado Aguirre

Abduction and induction are strictly related forms of defeasible reasoning. However, Machine Learning research is mainly focused on inductive techniques, leading from specific examples to general rules, with applications to classification, diagnosis and program synthesis.. Abduction has been used in Machine Learning, but its use was typically an aside technique, to be integrated or added on top of the basic inductive scheme. We discuss the general relation between abductive and inductive reasoning, showing that they solve different instantiations of the same problem. Then we analyze the specific ways abbdution has been used in Machine Learning. Two different cases are individuated: (1) abductive reasoning used in explanation-based learning systems as a heuristic to guide search in top-down specialization, and (2) abduction used for generating missing examples in relational learning. In both cases, the use of abduction is not general and adapted to a very tiny and specific problem. In this sense, the Machine Learning community has not used abduction as a synonym of induction, despite the high degree of similarity. However, both uses of abduction in learning have been proved to be effective for their intended purposes.

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Abduction and Induction in AI: Report of the IJCAI'97 Workshop
Antonis Kakas

Logic Journal of the Interest Group on Pure and …, 1998

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A Formal Logic for Abductive Reasoning
Diderik Batens

Logic Journal of IGPL, 2006

This paper presents and illustrates a formal logic for the abduction of singular hypotheses. The logic has a semantics and a dynamic proof theory that is sound and complete with respect to the semantics. The logic presupposes that, with respect to a specific application, the set of explananda and the set of possible explanantia are disjoint (but not necessarily exhaustive). Where an explanandum can be explained by different explanantia, the logic allows only for the abduction of their disjunction.

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References (20)

  1. Almeida, M. (1994). Diagndstico de fallas en sistemas distribuidos usando herramientas de Razonamiento Automdtico. MSc Thesis, ITESM, Monterrey, Mexico.
  2. Aguirre, J. L., Barr6n, O., Brena, R. and Garcfa, M. N. (1993). Using a high level knowledge representation for expert systems knowl- edge acquisition and prototyping, In Symposium on Applied Computing, SAC'93, Indianapolis.
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  13. Ince, D. (1984). Module interconnection languages and Prolog, ACM SIGPLAN Notices, Vol. 19(8).
  14. Jim6nez, G. (1993). Aplicacion del metodo logico de abduccion a la interrogacion de bases de datos relacionales. MSc Thesis, ITESM, Mexico.
  15. Luis-Castillo, C. (1997) Razonamiento automfitico abductivo en la soluci6n a consultas en lenguaje natural. MSc Thesis, ITESM, Mexico.
  16. Poole, D. (1994). Local users guide to Theorist. Vancouver: University of British Columbia.
  17. Poole, D. (1988). A logical framework for default reasoning. Artificial Intelligence, 36(1), 27-43.
  18. Poole, D. (1991). Compiling a default reasoning system into Prolog. New Generation Computing, 9, 3-38.
  19. Rice, M., & Seidman, S. (1994). A formal model for module interconnection languages. In IEEE Transactions on Software Engineering, Vol. 20(1).
  20. Steels, L. (1990). Components of Expertise. In AI Magazine, Summer, pp. 28-49.

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Abduction and Abductive Logic Programming
Paolo Mancarella
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Abduction-V2
Denis Zwirn

Abduction was first introduced by the philosopher C.S. Peirce in the epistemological context of scientific discovery. It was more recently analyzed in Artificial Intelligence, especially with respect to diagnosis analysis or ordinary reasoning. These two fields share a common view of abduction as a general process of hypotheses formation. More precisely, abduction is conceived as a kind of reverse explanation where a hypothesis H can be abduced from facts E if H is a "good explanation" of E. The paper aims at giving a general logical picture of abduction which could be used in both fields.

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A unified model for abduction-based reasoning
B. Ayeb

IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans, 1998

In the last decade, abduction has been a very active research area. This has resulted in a variety of models mechanizing abduction, namely within a probabilistic or logical framework. Recently, a few abductive models have been proposed within a neural framework. Unfortunately, these neural-/probablistic-/logical-based models cannot address complex abduction problems. In this paper, we propose a new extended neural-based model to deal with abduction problems which could be monotonic, open, and incompatible.

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Abduction is not Deduction-in-Reverse
F. Pirri

Logic Journal of IGPL, 1996

Abduction is a topic that attracts much interest in AI and automated reasoning research. Di erent approaches have been devised, that give a formalized account of explanatory reasoning, propose methods to compute explanations, frame abduction in the context of logic programming. However, the logical nature of abduction is still far from being clear and di erent speci cations of the key underlying concepts have been given, that make it di cult to speak of abduction as a single wellde ned form of reasoning. This work is a preliminary discussion on the logical nature of abductive reasoning, emphasizing the fundamental di erence between abductive and deductive inference. Some logical properties of the inference to the \best explanation" are put forward and analyzed when the underlying logic is any extension of classical propositional logic (rst order logic, modal logic) or a non monotonic system.

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Abduction from logic programs: Semantics and complexity
N. Leone

Theoretical Computer Science, 1997

Abduction{ from observations and a theory, nd using hypotheses an explanation for the observations { gained increasing interest during the last years. This form of reasoning has wide applicability in di erent areas of computer science; in particular, it has been recognized as an important principle of common-sense reasoning.

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