Case-Based Reasoning Technology

Case-Based Reasoning Technology PDF Author: Mario Lenz
Publisher: Springer
ISBN: 3540693513
Category : Computers
Languages : en
Pages : 405

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Book Description
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.

Case-Based Reasoning Technology

Case-Based Reasoning Technology PDF Author: Mario Lenz
Publisher: Springer
ISBN: 3540693513
Category : Computers
Languages : en
Pages : 405

Get Book Here

Book Description
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.

Case-based Reasoning

Case-based Reasoning PDF Author: Janet L. Kolodner
Publisher: Morgan Kaufmann
ISBN:
Category : Computers
Languages : en
Pages : 512

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Book Description


Case-Based Learning

Case-Based Learning PDF Author: Janet L. Kolodner
Publisher: Springer Science & Business Media
ISBN: 1461532280
Category : Computers
Languages : en
Pages : 171

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Book Description
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 Knowledge and Planning

Case-based Knowledge and Planning PDF Author: Itzhak Gilboa
Publisher:
ISBN:
Category : Decision making
Languages : en
Pages : 48

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Book Description


Issues and Applications of Case-Based Reasoning to Design

Issues and Applications of Case-Based Reasoning to Design PDF Author: Mary Lou Maher
Publisher: Psychology Press
ISBN: 131777891X
Category : Psychology
Languages : en
Pages : 355

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Book Description
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.

Case-Based Reasoning Research and Development

Case-Based Reasoning Research and Development PDF Author: Lorraine McGinty
Publisher: Springer Science & Business Media
ISBN: 3642029981
Category : Computers
Languages : en
Pages : 537

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Book Description
This book constitutes the refereed proceedings of the 8th International Conference on Case-Based Reasoning, ICCBR 2009, held in Seattle, WA, USA, in July 2009. The 17 revised full papers and 17 revised poster papers presented together with 2 invited talks were carefully reviewed and selected from 55 submissions. Covering a wide range of CBR topics of interest both to practitioners and researchers, the papers are devoted to theoretical/methodological as well as to applicative aspects of current CBR analysis.

Developing Industrial Case-Based Reasoning Applications

Developing Industrial Case-Based Reasoning Applications PDF Author: Ralph Bergmann
Publisher: Springer
ISBN: 3540409947
Category : Computers
Languages : en
Pages : 247

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Book Description
In just few years, case-based reasoning has evolved from a research topic studied at a small number of specialized academic labs into an industrial-strength technology applied in various fields. The INRECA methodology presented in detail in this monograph provides a data analysis framework for developing case-based reasoning solutions for successful applications in real-world industrial contexts. The book is divided into parts on: - smarter business with case-based decision support; - developing case-based applications using the INRECA methodology; and - using the methodology in various application domains. The book provides a self-contained introduction to case-based reasoning applications that address both R&D professionals and general IT managers interested in this powerful new technology. In this second edition, improvements and updates have been incorporated throughout the text. Particularly useful is the systematic coverage of experience factory applications at various steps; and, of course, the references have been extended substantially.

Knowledge-Based Process Planning for Construction and Manufacturing

Knowledge-Based Process Planning for Construction and Manufacturing PDF Author: Carlos Zozaya-Gorostiza
Publisher: Elsevier
ISBN: 0323156088
Category : Business & Economics
Languages : en
Pages : 320

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Book Description
Knowledge-Based Process Planning for Construction and Manufacturing describes a knowledge-based system architecture that is used to develop process planning systems called PLANEX. This book explains that PLANEX is a domain-independent, knowledge-based process planning system architecture. Starting from a description of the physical artifact to be constructed or manufactured, PLANEX generates the set of activities used to create the artifact. These activities, with their required resources, are linked into a process planning network which can be used in project scheduling or management. This text also reviews the concepts, requirements, and resulting architecture of PLANEX, including detailed descriptions of applications of the system in construction and manufacturing. This publication is recommended to engineers, architects, and specialists interested in construction and manufacturing process planning.

Case-Based Reasoning

Case-Based Reasoning PDF Author: Janet Kolodner
Publisher:
ISBN:
Category :
Languages : en
Pages : 0

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Book Description
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.

Knowledge Engineering Tools and Techniques for AI Planning

Knowledge Engineering Tools and Techniques for AI Planning PDF Author: Mauro Vallati
Publisher: Springer Nature
ISBN: 3030385612
Category : Computers
Languages : en
Pages : 277

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Book Description
This book presents a comprehensive review for Knowledge Engineering tools and techniques that can be used in Artificial Intelligence Planning and Scheduling. KE tools can be used to aid in the acquisition of knowledge and in the construction of domain models, which this book will illustrate. AI planning engines require a domain model which captures knowledge about how a particular domain works - e.g. the objects it contains and the available actions that can be used. However, encoding a planning domain model is not a straightforward task - a domain expert may be needed for their insight into the domain but this information must then be encoded in a suitable representation language. The development of such domain models is both time-consuming and error-prone. Due to these challenges, researchers have developed a number of automated tools and techniques to aid in the capture and representation of knowledge. This book targets researchers and professionals working in knowledge engineering, artificial intelligence and software engineering. Advanced-level students studying AI will also be interested in this book.