Download or read book Case based Reasoning written by David B. Leake and published by . This book was released on 1996 with total page 446 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Case based Reasoning written by Janet L. Kolodner and published by Morgan Kaufmann. This book was released on 1988 with total page 512 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Case Based Reasoning written by Michael M. Richter and published by Springer Science & Business Media. This book was released on 2013-10-31 with total page 550 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Applying Case Based Reasoning written by Ian Watson and published by Morgan Kaufmann. This book was released on 1997-07 with total page 318 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Case Based Reasoning Technology written by Mario Lenz and published by Springer. This book was released on 2003-05-20 with total page 405 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Soft Computing in Case Based Reasoning written by Sankar Kumar Pal and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Model Based Reasoning in Science and Technology written by Lorenzo Magnani and published by Springer. This book was released on 2016-07-01 with total page 678 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Case Based Reasoning Technology written by Mario Lenz and published by . This book was released on 2014-09-01 with total page 420 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Foundations of Soft Case Based Reasoning written by Sankar K. Pal and published by John Wiley & Sons. This book was released on 2004-07-01 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: Provides a self-contained description of this important aspect of information processing and decision support technology. Presents basic definitions, principles, applications, and a detailed bibliography. Covers a range of real-world examples including control, data mining, and pattern recognition.
Download or read book Case Based Learning written by Janet L. Kolodner and published by Springer Science & Business Media. This book was released on 1993-04-30 with total page 186 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Model Based Reasoning in Science and Technology written by Ángel Nepomuceno-Fernández and published by Springer Nature. This book was released on 2019-10-24 with total page 502 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Model Based Reasoning written by Lorenzo Magnani and published by Springer Science & Business Media. This book was released on 2002-05-31 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt: There are several key ingredients common to the various forms of model-based reasoning considered in this book. The term ‘model’ comprises both internal and external representations. The models are intended as interpretations of target physical systems, processes, phenomena, or situations and are retrieved or constructed on the basis of potentially satisfying salient constraints of the target domain. The book’s contributors are researchers active in the area of creative reasoning in science and technology.
Download or read book Case Based Reasoning in Design written by Mary Lou Maher and published by Psychology Press. This book was released on 2014-02-25 with total page 261 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Thinking about Android Epistemology written by Kenneth M. Ford and published by AAAI Press. This book was released on 2006 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: Articles by various authors arranged in 5 parts.
Download or read book Collaborative Learning Reasoning and Technology written by Angela M. O'Donnell and published by Routledge. This book was released on 2005-09-07 with total page 410 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume presents research findings on the use of technology to support learning and reasoning in collaborative contexts. Featuring a variety of theoretical perspectives, ranging from sociocultural to social psychological to information processing views, Collaborative Learning, Reasoning, and Technology includes an international group of authors
Download or read book Case Based Reasoning written by Isabelle Bichindaritz and published by Springer Science & Business Media. This book was released on 2010-07-07 with total page 554 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 18th International Conference on Case-Based Reasoning, held in Alessandria, Italy, in July 2010.
Download or read book Intelligent Systems for Engineers and Scientists written by Adrian A. Hopgood and published by CRC Press. This book was released on 2012-02-02 with total page 455 pages. Available in PDF, EPUB and Kindle. Book excerpt: The third edition of this bestseller examines the principles of artificial intelligence and their application to engineering and science, as well as techniques for developing intelligent systems to solve practical problems. Covering the full spectrum of intelligent systems techniques, it incorporates knowledge-based systems, computational intelligence, and their hybrids. Using clear and concise language, Intelligent Systems for Engineers and Scientists, Third Edition features updates and improvements throughout all chapters. It includes expanded and separated chapters on genetic algorithms and single-candidate optimization techniques, while the chapter on neural networks now covers spiking networks and a range of recurrent networks. The book also provides extended coverage of fuzzy logic, including type-2 and fuzzy control systems. Example programs using rules and uncertainty are presented in an industry-standard format, so that you can run them yourself. The first part of the book describes key techniques of artificial intelligence—including rule-based systems, Bayesian updating, certainty theory, fuzzy logic (types 1 and 2), frames, objects, agents, symbolic learning, case-based reasoning, genetic algorithms, optimization algorithms, neural networks, hybrids, and the Lisp and Prolog languages. The second part describes a wide range of practical applications in interpretation and diagnosis, design and selection, planning, and control. The author provides sufficient detail to help you develop your own intelligent systems for real applications. Whether you are building intelligent systems or you simply want to know more about them, this book provides you with detailed and up-to-date guidance. Check out the significantly expanded set of free web-based resources that support the book at: http://www.adrianhopgood.com/aitoolkit/
