abductive reasoning in artificial intelligence
Now the primary concern is how to keep AI rational yet logical. Deductive reasoning is used to reach a logical true conclusion. An example of the former is, “Fred must be in either the museum or the café. In this paper, I will outline an abductive logic programming (ALP) approach that aims to reconcile production rules and logic within a unifying agent-based framework. 121 Views 14 CrossRef citations to date Altmetric Listen. Original Articles The order effect in human abductive reasoning: an empirical and computational study. Authors: Mokanarangan Thayaparan, Marco Valentino, André Freitas. Abductive Reasoning in Science. Direction: Bottom up, starting with observations. L.B. View Profile. Another type of reasoning, inductive, is also used. Several researchers have studied abstract properties of nonmonotonic consequence relations (see for instance [6,7,15,16,19] ). The reader was introduced to the abduction and showed how it evolved historically within the conventional wisdom in logic. This process, unlike deductive reasoning, yields a plausible conclusion but does not positively verify it. Overview: Abductive Reasoning: Function: Logic. 107-164. 163-186 . Arizona State Univ., Tempe. Google Scholar. Abductive Artificial Intelligence Learning Models James A. Crowder and John N. Carbone Raytheon Intelligence, Information, and Services Aurora, Colorado 80011 Email: JACrowder@raytheon.com, John_N_Carbone@raytheon.com Abstract – There has been much research in recent years in the applicability of abductive reasoning to artificial intelligence and machine learning. Abductive reasoning is about filling the gap in a situation with missing information and then using best judgement to bridge the gap. The field of artificial intelligence has impacted many broad areas like gaming, agriculture, healthcare, finance, marketing, and many more.AI is capable of enhancing the productivity of humans and helping the entrepreneur to achieve goals rapidly. One can understand abductive reasoning as "inference to the best explanation". Abductive Reasoning: Logical Investigations into Discovery and Explanation is a much awaited original contribution to the study of abductive reasoning, providing logical foundations and a rich sample of pertinent applications. Abductive reasoning involves generating an explanation for a given set of observations about the world. Cases of causal explanations in law are analyzed using abductive reasoning, and all the components are finally brought together to build a new account of abductive reasoning. For example, if Jenny finds her house in a mess when she returns from work, and remembers that she left a window open, she can hypothesize that a thief broke into her house and caused the mess, as the most plausible explanation. Artificial intelligence - Artificial intelligence - Reasoning: To reason is to draw inferences appropriate to the situation. Both abduction and negation as failure are forms of non-monotonic reasoning. 102 (2) (1998), pp. In abductive reasoning, unlike in deductive reasoning, the premises do not guarantee the conclusion. 104 (1–2) (1998), pp. Submit an article Journal homepage. Journal of Experimental & Theoretical Artificial Intelligence Volume 23, 2011 - Issue 4. 5. Artificial Intelligence Review, (1989), 3, 129-158 Abductive reasoning in multiple fault diagnosis T. Finin & G. Morris*, Paoli Research Center, Unisys, Paoli, PA, USA and *AI Laboratory, Internal Revenue Service, Washington, DC, USA Abstract. The study of these high-levelmethods of abductive reasoning is situated at the crossroads of philosophy, logic, epistemology, artificial intelligence, neuroscience, cognitive psychology, animal cognition and evolutionary theories; that is, at the heart of cognitive science. The earliest attempts to formalise default reasoning in artificial intelligence employed non-logical, object-oriented representations, such as semantic networks and frames [Minsky, 1975]. For this purpose, an extended version of the semantic tableaux of chapter 4 provides a new representation of the operations of expansion, and contraction, all of which shapes the content of chapter 8. By clarifying the notion of abduction as a common and significant type of reasoning in everyday argumentation, Abductive Reasoning will be useful to scholars and students in many fields, including argumentation, computing and artificial intelligence, psychology and cognitive science, law, philosophy, linguistics, and speech communication and rhetoric. The reader is introduced to abduction and shown how it has evolved historically into the framework of conventional wisdom in logic. Download PDF Abstract: We propose a novel approach for answering and explaining multiple-choice science questions by reasoning on grounding … Abductive reasoning is used to access the concepts of things and define the possibilities of what can be achieved, inductive reasoning is used to develop destructive tests to confirm the limits of the validity of knowledge and deductive reasoning is used to develop validation tests and manage the operation. Artificial Intelligence, Vol. Artificial Intelligence 89 (1997) 149-171 Artificial Intelligence Abductive consequence relations Jorge Lobo a,*, Carlos Uidtegui b,l a ... consequence relation implicit in abductive reasoning rather than in the selection of the explanations. Abductive learning … Arizona State Univ., Tempe. Abductive Reasoning: Challenges Ahead 263 argue that abduction viewed in this way can model dynamics of belief revision in artificial intelligence. This book examines three areas in which abductive reasoning is especially important: medicine, science, and law. For most scientists, abductive reasoning is a natural and instinctive process, a series of educated guesses, building upon observed phenomena and previous studies. Image Source . Thirteenth Artificial Intelligence and Interactive Digital Entertainment Conference (94) Thirteenth International Conference on the Principles of Knowledge Representation and Reasoning (74) Thirtieth AAAI Conference on Artificial Intelligence (669) Thirty-First AAAI Conference on Artificial Intelligence (749) The fields of law, computer science, and artificial intelligence research renewed interest in the subject of abduction. It is useful in Artificial Intelligence applications for natural language understanding, default reasoning, knowledge assimilation, belief revision, and very useful in multi-agent systems . Abductive learning involves finding the best explanation for a set of observations, based on creating a set of possible explanatory hypotheses. Crossref Andrew Csinger, Kellogg S. Booth, David Poole, AI Meets Authoring: User Models for Intelligent Multimedia, Integration of Natural Language and Vision Processing, 10.1007/978-94-011-0273-5, (283-304), (1995). Daniele Theseider Dupré, Mauro Rossotto, The different roles of abstraction in abductive reasoning, Topics in Artificial Intelligence, 10.1007/3-540-60437-5_20, (211-216), (1995).
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