Case-Based Reasoning in Design
Case-Based Reasoning in Design

Author: Mary Lou Maher

Publisher: Psychology Press

Published: 2014-02-25

Total Pages: 261

ISBN-13: 1317779754

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Case-based reasoning in design is becoming an important approach to computer-support for design as well as an important component in understanding the design process. Design has become a major focus for problem solving paradigms due to its complexity and open-ended nature. This book presents a clear description of how case-based reasoning can be applied to design problems, including the representation of design cases, indexing and retrieving design cases, and the range of paradigms for adapting design cases. With a focus on design, this book differs from others that provide a generalist view of case-based reasoning. This volume provides two important contributions to the area: * a general description of the issues and alternatives in applying case-based reasoning to design, and * a description of specific implementations of case-based design. Through this combination, the reader will learn about both the general issues and the practical problems in supporting design through case-based reasoning. This book was prepared to fill a gap in the literature on the unique problems that design introduces to computational paradigms developed in computer science. It also addresses the needs of computational support for design problem solving from both theoretical and practical perspectives.

Issues and Applications of Case-Based Reasoning to Design
Issues and Applications of Case-Based Reasoning to Design

Author: Mary Lou Maher

Publisher: Psychology Press

Published: 2014-02-25

Total Pages: 382

ISBN-13: 1317778901

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Design is believed to be one of the most interesting and challenging problem-solving activities ever facing artificial intelligence (AI) researchers. Knowledge-based systems using rule-based and model-based reasoning techniques have been applied to build design automation and/or design decision support systems. Although such systems have met with some success, difficulties have been encountered in terms of formalizing such generalized design experiences as rules, logic, and domain models. Recently, researchers have been exploring the idea of using case-based reasoning (CBR) techniques to complement or replace other approaches to design support. CBR can be considered as an alternative to paradigms such as rule-based and model-based reasoning. Rule-based expert systems capture knowledge in the form of if-then rules which are usually identified by a domain expert. Model-based reasoning aims at formulating knowledge in the form of principles to cover the various aspects of a problem domain. These principles, which are more general than if-then rules, comprise a model which an expert system may use to solve problems. Model-based reasoning (MBR) is sometimes called reasoning from first principles. Instead of generalizing knowledge into rules or models, CBR is an experience-based method. Thus, specific cases, corresponding to prior problem-solving experiences, comprise the main knowledge sources in a CBR system. This volume includes a collection of chapters that describe specific projects in which case-based reasoning is the focus for the representation and reasoning in a particular design domain. The chapters provide a broad spectrum of applications and issues in applying and extending the concept of CBR to design. Each chapter provides its own introduction to CBR concepts and principles.

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.

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 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.

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.

Case-Based Reasoning in Design
Case-Based Reasoning in Design

Author: Mary Lou Maher

Publisher: Psychology Press

Published: 2014-02-25

Total Pages: 268

ISBN-13: 1317779746

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Case-based reasoning in design is becoming an important approach to computer-support for design as well as an important component in understanding the design process. Design has become a major focus for problem solving paradigms due to its complexity and open-ended nature. This book presents a clear description of how case-based reasoning can be applied to design problems, including the representation of design cases, indexing and retrieving design cases, and the range of paradigms for adapting design cases. With a focus on design, this book differs from others that provide a generalist view of case-based reasoning. This volume provides two important contributions to the area: * a general description of the issues and alternatives in applying case-based reasoning to design, and * a description of specific implementations of case-based design. Through this combination, the reader will learn about both the general issues and the practical problems in supporting design through case-based reasoning. This book was prepared to fill a gap in the literature on the unique problems that design introduces to computational paradigms developed in computer science. It also addresses the needs of computational support for design problem solving from both theoretical and practical perspectives.

Encyclopedia of Machine Learning
Encyclopedia of Machine Learning

Author: Claude Sammut

Publisher: Springer Science & Business Media

Published: 2011-03-28

Total Pages: 1061

ISBN-13: 0387307680

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This comprehensive encyclopedia, in A-Z format, provides easy access to relevant information for those seeking entry into any aspect within the broad field of Machine Learning. Most of the entries in this preeminent work include useful literature references.

Intelligent Systems for Engineering
Intelligent Systems for Engineering

Author: Ram D. Sriram

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 843

ISBN-13: 1447106318

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When men of knowledge impart this knowledge, I do not mean they will convince your reason. I mean they will awaken in you the faith that it is so. - Sri Krishna, Bhagavadgita BACKGROUND The use of computers has led to significant productivity increases in the en gineering industry. Most ofthe computer-aided engineering applications were . restricted to algorithmic computations, such as finite element programs and circuit analysis programs. However, a number ofproblems encountered in en gineering are not amenable to purely algorithmic solutions. These problems are often ill-structured; the term ill-structured problems is used here to de note problems that do not have a clearly defined algorithmic solution. An experienced engineer deals with these ill-structured problems using his/her judgment and experience. The knowledge-based systems (KBS) technology, which emerged out of research in artificial intelligence (AI), offers a method ologyto solve these ill-structuredengineering problems. The emergenceofthe KBS technology can be viewed as the knowledge revolution: other important events that led to increased productivity are the industrial revolution (17th century); the invention of the transistor and associated developments (first half of the 20th century); and the world-wide web (towards the end of the 20th century). Kurzweil, in a lecture at M. LT on December 3, 1987, linked the progress of automation to two industrial revolutions: the first industrial PREFACE xxxii revolution leveraged our physical capabilities, whereas the second industrial revolution - the knowledge revolution - is expected leverage oUr mental ca pabilities.

Case-Based Reasoning Research and Development
Case-Based Reasoning Research and Development

Author: David W. Aha

Publisher: Springer

Published: 2003-05-15

Total Pages: 769

ISBN-13: 3540445935

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The 2001 International Conference on Case-Based Reasoning (ICCBR 2001, www.iccbr.org/iccbr01), the fourth in the biennial ICCBR series (1995 in Sesimbra, Portugal; 1997 in Providence, Rhode Island (USA); 1999 in Seeon, Germany), was held during 30 July – 2 August 2001 in Vancouver, Canada. ICCBR is the premier international forum for researchers and practitioners of case based reasoning (CBR). The objectives of this meeting were to nurture significant, relevant advances made in this field (both in research and application), communicate them among all attendees, inspire future advances, and continue to support the vision that CBR is a valuable process in many research disciplines, both computational and otherwise. ICCBR 2001 was the first ICCBR meeting held on the Pacific coast, and we used the setting of beautiful Vancouver as an opportunity to enhance participation from the Pacific Rim communities, which contributed 28% of the submissions. During this meeting, we were fortunate to host invited talks by Ralph Bergmann, Ken Forbus, Jaiwei Han, Ramon López de Mántaras, and Manuela Veloso. Their contributions ensured a stimulating meeting; we thank them all.