Case-Based Reasoning
Case-Based Reasoning

Author: Janet Kolodner

Publisher: Morgan Kaufmann

Published: 2014-06-28

Total Pages: 687

ISBN-13: 1483294498

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Case-based reasoning is one of the fastest growing areas in the field of knowledge-based systems and this book, authored by a leader in the field, is the first comprehensive text on the subject. Case-based reasoning systems are systems that store information about situations in their memory. As new problems arise, similar situations are searched out to help solve these problems. Problems are understood and inferences are made by finding the closest cases in memory, comparing and contrasting the problem with those cases, making inferences based on those comparisons, and asking questions when inferences can't be made. This book presents the state of the art in case-based reasoning. The author synthesizes and analyzes a broad range of approaches, with special emphasis on applying case-based reasoning to complex real-world problem-solving tasks such as medical diagnosis, design, conflict resolution, and planning. The author's approach combines cognitive science and engineering, and is based on analysis of both expert and common-sense tasks. Guidelines for building case-based expert systems are provided, such as how to represent knowledge in cases, how to index cases for accessibility, how to implement retrieval processes for efficiency, and how to adapt old solutions to fit new situations. This book is an excellent text for courses and tutorials on case-based reasoning. It is also a useful resource for computer professionals and cognitive scientists interested in learning more about this fast-growing field.

Applying Case-Based Reasoning
Applying Case-Based Reasoning

Author: Ian Watson

Publisher: Morgan Kaufmann

Published: 1997-07

Total Pages: 318

ISBN-13:

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This book explains the principles of CBR by describing its origin and contrasting it with familiar information disciplines such as traditional data processing, logic programming, rule-based expert systems, and object-oriented programming. Through case studies and step-by-step examples, this book shows programmers and software managers how to design and implement a reliable, robust CBR system in a real-world environment.

Case-Based Reasoning
Case-Based Reasoning

Author: Michael M. Richter

Publisher: Springer Science & Business Media

Published: 2013-10-31

Total Pages: 550

ISBN-13: 3642401678

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This book presents case-based reasoning in a systematic approach with two goals: to present rigorous and formally valid structures for precise case-based reasoning, and to demonstrate the range of techniques, methods, and tools available for many applications.

Handbook of Software Engineering & Knowledge Engineering
Handbook of Software Engineering & Knowledge Engineering

Author: Shi Kuo Chang

Publisher: World Scientific

Published: 2002

Total Pages: 807

ISBN-13: 9810249748

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This is the first handbook to cover comprehensively both software engineering and knowledge engineering -- two important fields that have become interwoven in recent years. Over 60 international experts have contributed to the book. Each chapter has been written in such a way that a practitioner of software engineering and knowledge engineering can easily understand and obtain useful information. Each chapter covers one topic and can be read independently of other chapters, providing both a general survey of the topic and an in-depth exposition of the state of the art. Practitioners will find this handbook useful when looking for solutions to practical problems. Researchers can use it for quick access to the background, current trends and most important references regarding a certain topic.The handbook consists of two volumes. Volume One covers the basic principles and applications of software engineering and knowledge engineering.Volume Two will cover the basic principles and applications of visual and multimedia software engineering, knowledge engineering, data mining for software knowledge, and emerging topics in software engineering and knowledge engineering.

Model-Based Reasoning in Science and Technology
Model-Based Reasoning in Science and Technology

Author: Lorenzo Magnani

Publisher: Springer

Published: 2016-07-01

Total Pages: 674

ISBN-13: 3319389831

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This book discusses how scientific and other types of cognition make use of models, abduction, and explanatory reasoning in order to produce important or creative changes in theories and concepts. It includes revised contributions presented during the international conference on Model-Based Reasoning (MBR’015), held on June 25-27 in Sestri Levante, Italy. The book is divided into three main parts, the first of which focuses on models, reasoning and representation. It highlights key theoretical concepts from an applied perspective, addressing issues concerning information visualization, experimental methods and design. The second part goes a step further, examining abduction, problem solving and reasoning. The respective contributions analyze different types of reasoning, discussing various concepts of inference and creativity and their relationship with experimental data. In turn, the third part reports on a number of historical, epistemological and technological issues. By analyzing possible contradictions in modern research and describing representative case studies in experimental research, this part aims at fostering new discussions and stimulating new ideas. All in all, the book provides researchers and graduate students in the field of applied philosophy, epistemology, cognitive science and artificial intelligence alike with an authoritative snapshot of current theories and applications of model-based reasoning.

Case-Based Learning
Case-Based Learning

Author: Janet L. Kolodner

Publisher: Springer Science & Business Media

Published: 1993-04-30

Total Pages: 186

ISBN-13: 9780792393436

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Case-based reasoning means reasoning based on remembering previous experiences. A reasoner using old experiences (cases) might use those cases to suggest solutions to problems, to point out potential problems with a solution being computed, to interpret a new situation and make predictions about what might happen, or to create arguments justifying some conclusion. A case-based reasoner solves new problems by remembering old situations and adapting their solutions. It interprets new situations by remembering old similar situations and comparing and contrasting the new one to old ones to see where it fits best. Case-based reasoning combines reasoning with learning. It spans the whole reasoning cycle. A situation is experienced. Old situations are used to understand it. Old situations are used to solve a problem (if there is one to be solved). Then the new situation is inserted into memory alongside the cases it used for reasoning, to be used another time. The key to this reasoning method, then, is remembering. Remembering has two parts: integrating cases or experiences into memory when they happen and recalling them in appropriate situations later on. The case-based reasoning community calls this related set of issues the indexing problem. In broad terms, it means finding in memory the experience closest to a new situation. In narrower terms, it can be described as a two-part problem: assigning indexes or labels to experiences when they are put into memory that describe the situations to which they are applicable, so that they can be recalled later; and at recall time, elaborating the new situation in enough detail so that the indexes it would have if it were in the memory are identified. Case-Based Learning is an edited volume of original research comprising invited contributions by leading workers. This work has also been published as a special issues of MACHINE LEARNING, Volume 10, No. 3.

Soft Computing in Case Based Reasoning
Soft Computing in Case Based Reasoning

Author: Sankar Kumar Pal

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 380

ISBN-13: 1447106873

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This text demonstrates how various soft computing tools can be applied to design and develop methodologies and systems with case based reasoning, that is, for real-life decision-making or recognition problems. Comprising contributions from experts, it introduces the basic concepts and theories, and includes many reports on real-life applications. This book is of interest to graduate students and researchers in computer science, electrical engineering and information technology, as well as researchers and practitioners from the fields of systems design, pattern recognition and data mining.

Case-Based Reasoning Technology
Case-Based Reasoning Technology

Author: Mario Lenz

Publisher: Springer

Published: 2003-05-20

Total Pages: 414

ISBN-13: 3540693513

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This state-of-the-art survey presents a coherent summary of research and development in case-based reasoning (CBR) undertaken in Germany in recent years. The book opens with a general introduction to CBR presenting the basic ideas and concepts, setting the terminology, and looking at CBR from some new points of view. The main part of the book, consisting of nine chapters, is devoted to detailed presentations of CBR applications successfully performed in various areas. Among these application areas are decision and sales support, text processing, adaptation, planning, design, software engineering, tutoring systems, and medicine. The remaining chapters present areas related to CBR as well as a glossary, a subject index and bibliography.

Model-Based Reasoning in Science and Technology
Model-Based Reasoning in Science and Technology

Author: Ángel Nepomuceno-Fernández

Publisher: Springer Nature

Published: 2019-10-24

Total Pages: 510

ISBN-13: 3030327221

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This book discusses how scientific and other types of cognition make use of models, abduction, and explanatory reasoning in order to produce important and innovative changes in theories and concepts. Gathering revised contributions presented at the international conference on Model-Based Reasoning (MBR18), held on October 24–26 2018 in Seville, Spain, the book is divided into three main parts. The first focuses on models, reasoning, and representation. It highlights key theoretical concepts from an applied perspective, and addresses issues concerning information visualization, experimental methods, and design. The second part goes a step further, examining abduction, problem solving, and reasoning. The respective papers assess different types of reasoning, and discuss various concepts of inference and creativity and their relationship with experimental data. In turn, the third part reports on a number of epistemological and technological issues. By analyzing possible contradictions in modern research and describing representative case studies, this part is intended to foster new discussions and stimulate new ideas. All in all, the book provides researchers and graduate students in the fields of applied philosophy, epistemology, cognitive science, and artificial intelligence alike with an authoritative snapshot of the latest theories and applications of model-based reasoning.

Case-based Reasoning
Case-based Reasoning

Author: David B. Leake

Publisher:

Published: 1996

Total Pages: 446

ISBN-13:

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It also presents lessons learned about how to design CBR systems and how to apply them to real-world problems. The final chapters include a perspective on the state of the field and the most important directions for future impact.