6 edition of **Abductive inference models for diagnostic problem-solving** found in the catalog.

- 111 Want to read
- 36 Currently reading

Published
**1990**
by Springer-Verlag in New York
.

Written in English

- Artificial intelligence,
- Problem solving,
- Abduction (Logic),
- Reasoning

**Edition Notes**

Includes bibliographical references (p. [269]-278) and index.

Statement | Yun Peng, James A. Reggia. |

Series | Symbolic computation. |

Contributions | Reggia, James A. |

Classifications | |
---|---|

LC Classifications | Q335 .P414 1990 |

The Physical Object | |

Pagination | xii, 284 p. : |

Number of Pages | 284 |

ID Numbers | |

Open Library | OL1876566M |

ISBN 10 | 0387973435 |

LC Control Number | 90036687 |

Abductive inference models for diagnostic problem-solving Yun Peng Univ. of Maryland, College Park; and The Institute of Software, Academia Sinica, Beijing, China. This book contains leading survey papers on the various aspects of Abduction, both logical and numerical approaches. Abduction is central to all areas of applied reasoning, including artificial intelligence, philosophy of science, machine learning, data mining and decision theory, as well as.

Complete Book Stationary Power Techniques Garmin Zumo Motorcycle Gps Understanding Myself A Kids Guide To Intense Emotions And Strong Feelings Abductive Inference Models For Diagnostic Problem Solving Symbolic Computation Amercian Cinema Amercian Culture 89 Trooper Repair Manual. Abductive reasoning (also called abduction, [1] abductive inference, [1] or retroduction [2]) is a form of logical inference that starts with an observation or set of observations and then seeks to find the simplest and most likely conclusion from the observations. This process, unlike deductive reasoning, yields a plausible conclusion but does not positively verify it.

Book Name Author(s) Abductive Inference Models for Diagnostic Problem-Solving 1st Edition 0 Problems solved: S. Amarel, Alan Bundy, Herve Gallaire, Guided textbook solutions created by Chegg experts Learn from step-by-step solutions for o ISBNs in Math, Science, Engineering, Business and more. Abductive Reasoning: Philosophical and Educational Perspectives in Medicine. Lorenzo Magnani. Department of Philosophy. University of Pavia (Italy) The aim of this paper is to emphasize the significance of abduction in order to illustrate the problem solving process and to propose a unified epistemological model of medical reasoning.

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Abductive Inference Models for Diagnostic Problem-Solving. Authors (view affiliations) Yun Peng; James A. Reggia; Book. Computational Models for Diagnostic Problem Solving. Yun Peng, James A. Reggia. Pages diagnostic reasoning can be classified as a type of inf- ence known as abductive reasoning or abduction.

Abduction is defined. Abductive reasoning / abductive inference is an unheralded, but highly important branch of logic. There is reason to think that much of human reasoning is abductive in nature, making this a key area of artificial intelligence research. Thinking systems that act somewhat human-like will almost certainly incorporate some element of abductive 5/5(1).

Abductive Inference Models for Diagnostic Problem-Solving. Authors: Peng, Yun, Reggia, James A. Free PreviewBrand: Springer-Verlag New York. Abductive Inference Models for Diagnostic Problem-Solving (Symbolic Computation) [Peng, Yun, Reggia, James A.] on *FREE* shipping on qualifying offers.

Abductive inference models for diagnostic problem-solving book Abductive Inference Models for Diagnostic Problem-Solving (Symbolic Computation)Cited by: Get this from a library. Abductive Inference Models for Diagnostic Problem-Solving. [Yun Peng; James A Reggia] -- This book is about reasoning with causal associations during diagnostic problem-solving.

It formalizes several currently vague notions of abductive inference in the context of diagnosis. The result. Get this from a library. Abductive inference models for diagnostic problem-solving. [Yun Peng; James A Reggia]. In the probabilistic causal model described in this book, as well as in some others, probabilistic inference is combined with AI symbol processing methods for diagnostic problem-solving.

In these models disorders and manifestations (and perhaps intermediate states) are connected by causal links associated with probabilities representing the Author: Yun Peng, Yun Peng, James A. Reggia. This book is about reasoning with causal associations during diagnostic problem-solving.

It formalizes several currently vague notions of abductive inference in the context of diagnosis. The result is a mathematical model of diagnostic reasoning called parsimonious covering theory.

Abductive Inference Models for Diagnostic Problem-Solving by Yun Peng,available at Book Depository with free delivery worldwide.

One of the well developed abductive inference models for diagnostic problem solving was proposed by Peng and Reggia 2, 3 by integrating formal probability theory into the frame of the parsimonious set covering theory.

In their work, the most salient contribution is the development of a probability criterion for describing the plausibility of a Cited by: 6. Logic-Based Abductive Inference.

the book also contains many illustrative examples and problems. The text is intended to be self-contained, the. Read "Book review: Abduetive Inference Models for Diagnostic Problem Solving by Y. Peng and J. Reggia (Springer Verlag New York ), ACM SIGART Bulletin" on DeepDyve, the largest online rental service for scholarly research with thousands.

Neural Network Models for Abduction Problems Solving The training procedure is different for different abduction problems in the [2] approach, and it. But we will now show that some abductive inference is better understood as using pictorial or other iconic representations.

Visual abduction Abductive inference models for diagnostic problem solving. Springer Verlag, New York, N.Y., [22] R. Reiter. A theory of diagnosis from first principles. Artificial Intelligence, Buy (ebook) Abductive Inference Models for Diagnostic Problem-Solving by James A.

Reggia, Yun Peng, eBook format, from the Dymocks online bookstore. This model uses an abductive inference mechanism based on the parsimonious covering theory, and adds some new features to the general model of diagnostic problem-solving. The network fault-diagnosis knowledge is assumed to be represented in the form of causal chaining, namely, a hyper-bipartite by: 7.

Abductive reasoning is a specific-to-general form of reasoning that specifically looks at cause and effect. Key Terms. logic: Step-by-step thinking about how a problem can be solved or a conclusion can be reached.

inference: A conclusion drawn from true or assumed-true facts. Thagard P () Book review: Abduetive Inference Models for Diagnostic Problem Solving by Y. Peng and J. Reggia (Springer Verlag New York ), ACM SIGART Bulletin,(), Online publication date: 1-Nov S Amarel Solutions.

Below are Chegg supported textbooks by S Amarel. Select a textbook to see worked-out Solutions. Books by S Amarel with Solutions.

Book Name Author(s) Abductive Inference Models for Diagnostic Problem-Solving 1st Edition 0. [J1] Josephson J, Josephson S. Abductive Inference, Cambridge University Press, [L1] Lapizco-Encinas G, Reggia J.

Diagnostic Problem Solving Using Swarm Intelligence, Proc. IEEE Swarm Intelligence Symposium,[N1] Neapolitan R. Learning Bayesian Networks, Prentice Hall, [P1] Patokorpi E.

He and Yun Peng wrote a very accessible book on the subject - Abductive Inference Models for Diagnostic Problem Solving.

And to add to what JahKnows says - I'd say that where something like deep-learning would be most likely to come into play, would be building the initial knowledgebase that is used in the diagnostic system.What is Abductive Reasoning? Meaning. Abductive Reasoning is a reasoning process that starts from observing facts, leading via intuition to a hypothesis, which is considered a viable explanation.

The concept of Abductive Reasoning was initially developed by American philosopher, mathematician and scientist Charles Sanders Pierce () in the early .Abductive reasoning is to abduce (or take away) a logical assumption, explanation, inference, conclusion, hypothesis, or best guess from an observation or set of observations.

Because the.