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Abductive reasoning

About: Abductive reasoning is a research topic. Over the lifetime, 1917 publications have been published within this topic receiving 44645 citations. The topic is also known as: abduction & abductive inference.


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Book ChapterDOI
06 Oct 1993
TL;DR: A unified approach to three important areas of AI: nonmonotonic logics, belief revision theories, and belief revision systems is presented, using an implementation of a belief revision system based on the logic and the belief revision theory to illustrate these formalisms.
Abstract: We present a unified approach to three important areas of AI: nonmonotonic logics, belief revision theories, and belief revision systems. The nonmonotonic logic we present, SWMC, is appropriate to support belief revision systems, because it keeps a track of dependencies between formulas. Another distinguishing feature of SWMC is the distinction between what follows soundly from a set of premises, and what can plausibly be concluded. In what concerns belief revision theories, we present a theory based on a nonmonotonic logic, SWMC, which, to the best of our knowledge, is a novel approach. Finally, we use an implementation of a belief revision system based on the logic and the belief revision theory, to illustrate these formalisms.

3 citations

Journal Article
TL;DR: It is maintained that abductive inference strategies must be used in a Creative Teaching-learning Program for gifted science students because generative hypotheses of this hypothetic deductive methodology are not manifest.
Abstract: The purpose of this research is to propose a program for teaching and learning effective problem-solving for gifted students based on abductive inference. The role of abductive inference is important for scientific discoveries and creative inferences in problem-solving processes. The characteristics of creativity and abductive inference were investigated, and the following were discussed: (a) a suggestion for a new program based on abductive inference for creative outcomes, this program largely consists of two phases: generative hypotheses and confirmative hypotheses, (b) a survey of the validity of a program. It is typical that hypotheses are confirmed in phases through experiments based on hypothetic deductive methodology. However, because generative hypotheses of this hypothetic deductive methodology are not manifest, we maintained that abductive inference strategies must be used in a Creative Teaching-learning Program for gifted science students.

3 citations

Journal Article
TL;DR: The three main semantics for fuzzy sets: similarity, preference and uncertainty are emphasized and potentials of fuzzy set-based reasoning methods are briefly outlined for various kinds of approximate reasoning.
Abstract: This short paper about fuzzy set-based approximate reasoning first emphasizes the three main semantics for fuzzy sets: similarity, preference and uncertainty. The difference between truth-functional many-valued logics of vague or gradual propositions and non fully compositional calculi such as possibilistic logic (which handles uncertainty) or similarity logics is stressed. Then, potentials of fuzzy set-based reasoning methods are briefly outlined for various kinds of approximate reasoning: deductive reasoning about flexible constraints, reasoning under uncertainty and inconsistency, hypothetical reasoning, exception-tolerant plausible reasoning using generic knowledge, interpolative reasoning, and abductive reasoning (under uncertainty). Open problems are listed in the conclusion.

3 citations

Book
05 Apr 2000
TL;DR: In this article, the authors discuss the nature of argument in logic and arguments in Ordinary Discourse, and the centrality of reasoning in the law. But they do not discuss the role of logic in the analysis of cases.
Abstract: PART I: ELEMENTS OF REASONING. 1. Statements. Words. Meaning and Definition. Sentences, Language Uses, and Truth. 2. Arguments. The Nature of Arguing. Arguments in Logic and Arguments in Ordinary Discourse. Kinds of Argument: Deductive v. Inductive Reasoning. Deductive Reasoning and Methods of Appraising Validity. Inductive Reasoning and Methods of Appraising Strength. PART II: ELEMENTS OF LEGAL REASONING. 3. Reasoning and the Law. The Centrality of Reasoning in the Law. Deductive Reasoning and the Law. Inductive Reasoning and the Law. How Judges Reason. PART III: CASE ANALYSIS. 4. Guidelines for Analysing Cases. The Written Opinion. The Elements of a Written Opinion. 5. Analyzing Cases. Riggs v. Palmer. Analysis of Riggs v. Palmer. Palsgraf v. Long Island Railroad. Analysis of Palsgraf v. Long Island Railroad. Appendix I: Guidelines for Writing Argumentative Papers. Appendix II: Legal Fundamentals.

3 citations

Journal ArticleDOI
01 Sep 1994
TL;DR: A new proposal for the computation of hypotheses in an abductive framework where the theory is a general logic program, based on a suitable manipulation of minimal three-valued models of the logic program is presented.
Abstract: Logic programming with abductive reasoning is used during the realization of a data dictionary with a particular methodology. Some methodological steps are represented by means of a set ofrules augmented with integrity constraints which capture the presence of incompatible concepts. Explanations for incompatibility can be inferred by exploiting abductive reasoning . To this end a new proposal for the computation of hypotheses in an abductive framework where the theory is a general logic program, is presented. It is based on a suitable manipulation of minimal three-valued models of the logic program. A method to compute three-valued minimal models of a general logic program is given.

3 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202356
2022103
202156
202059
201956
201867