Multistrategy Learning

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Multistrategy Learning

Author : Ryszard S. Michalski
Publisher : Springer Science & Business Media
ISBN 13 : 9780792393740
Total Pages : 174 pages
Book Rating : 4.3/5 (937 download)

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Book Synopsis Multistrategy Learning by : Ryszard S. Michalski

Download or read book Multistrategy Learning written by Ryszard S. Michalski and published by Springer Science & Business Media. This book was released on 1993-06-30 with total page 174 pages. Available in PDF, EPUB and Kindle. Book excerpt: Most machine learning research has been concerned with the development of systems that implememnt one type of inference within a single representational paradigm. Such systems, which can be called monostrategy learning systems, include those for empirical induction of decision trees or rules, explanation-based generalization, neural net learning from examples, genetic algorithm-based learning, and others. Monostrategy learning systems can be very effective and useful if learning problems to which they are applied are sufficiently narrowly defined. Many real-world applications, however, pose learning problems that go beyond the capability of monostrategy learning methods. In view of this, recent years have witnessed a growing interest in developing multistrategy systems, which integrate two or more inference types and/or paradigms within one learning system. Such multistrategy systems take advantage of the complementarity of different inference types or representational mechanisms. Therefore, they have a potential to be more versatile and more powerful than monostrategy systems. On the other hand, due to their greater complexity, their development is significantly more difficult and represents a new great challenge to the machine learning community. Multistrategy Learning contains contributions characteristic of the current research in this area.

Multistrategy Learning

Author : Ryszard S. Michalski
Publisher : Springer Science & Business Media
ISBN 13 : 1461532027
Total Pages : 156 pages
Book Rating : 4.4/5 (615 download)

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Book Synopsis Multistrategy Learning by : Ryszard S. Michalski

Download or read book Multistrategy Learning written by Ryszard S. Michalski and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 156 pages. Available in PDF, EPUB and Kindle. Book excerpt: Most machine learning research has been concerned with the development of systems that implememnt one type of inference within a single representational paradigm. Such systems, which can be called monostrategy learning systems, include those for empirical induction of decision trees or rules, explanation-based generalization, neural net learning from examples, genetic algorithm-based learning, and others. Monostrategy learning systems can be very effective and useful if learning problems to which they are applied are sufficiently narrowly defined. Many real-world applications, however, pose learning problems that go beyond the capability of monostrategy learning methods. In view of this, recent years have witnessed a growing interest in developing multistrategy systems, which integrate two or more inference types and/or paradigms within one learning system. Such multistrategy systems take advantage of the complementarity of different inference types or representational mechanisms. Therefore, they have a potential to be more versatile and more powerful than monostrategy systems. On the other hand, due to their greater complexity, their development is significantly more difficult and represents a new great challenge to the machine learning community. Multistrategy Learning contains contributions characteristic of the current research in this area.

Machine Learning

Author : Ryszard S. Michalski
Publisher : Morgan Kaufmann
ISBN 13 : 9781558602519
Total Pages : 798 pages
Book Rating : 4.6/5 (25 download)

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Book Synopsis Machine Learning by : Ryszard S. Michalski

Download or read book Machine Learning written by Ryszard S. Michalski and published by Morgan Kaufmann. This book was released on 1994-02-09 with total page 798 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multistrategy learning is one of the newest and most promising research directions in the development of machine learning systems. The objectives of research in this area are to study trade-offs between different learning strategies and to develop learning systems that employ multiple types of inference or computational paradigms in a learning process. Multistrategy systems offer significant advantages over monostrategy systems. They are more flexible in the type of input they can learn from and the type of knowledge they can acquire. As a consequence, multistrategy systems have the potential to be applicable to a wide range of practical problems. This volume is the first book in this fast growing field. It contains a selection of contributions by leading researchers specializing in this area. See below for earlier volumes in the series.

Multistrategy Learning

Author : Ryszard Stanisław Michalski
Publisher :
ISBN 13 :
Total Pages : 136 pages
Book Rating : 4.:/5 (521 download)

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Book Synopsis Multistrategy Learning by : Ryszard Stanisław Michalski

Download or read book Multistrategy Learning written by Ryszard Stanisław Michalski and published by . This book was released on 2003 with total page 136 pages. Available in PDF, EPUB and Kindle. Book excerpt:

The Mathematical Foundation of Multi-Space Learning Theory

Author : Tai Wang
Publisher : Taylor & Francis
ISBN 13 : 1003853803
Total Pages : 137 pages
Book Rating : 4.0/5 (38 download)

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Book Synopsis The Mathematical Foundation of Multi-Space Learning Theory by : Tai Wang

Download or read book The Mathematical Foundation of Multi-Space Learning Theory written by Tai Wang and published by Taylor & Francis. This book was released on 2024-03-12 with total page 137 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explores the measurement of learning effectiveness and the optimization of knowledge retention by modeling the learning process and building the mathematical foundation of multi-space learning theory. Multi-space learning is defined in this book as a micro-process of human learning that can take place in more than one space, with the goal of effective learning and knowledge retention. This book models the learning process as a temporal sequence of concept learning, drawing on established principles and empirical evidence. It also introduces the matroid to strengthen the mathematical foundation of multi-space learning theory and applies the theory to vocabulary and mathematics learning, respectively. The results show that, for vocabulary learning, the method can be used to estimate the effectiveness of a single learning strategy, to detect the mutual interference that might exist between learning strategies, and to predict the optimal combination of strategies. In mathematical learning, it was found that timing is crucial in both first learning and second learning in scheduling optimization to maximize the intersection effective interval. The title will be of interest to researchers and students in a wide range of areas, including educational technology, learning sciences, mathematical applications, and mathematical psychology.

Adaption and Learning in Multi-agent Systems

Author : Gerhard Weiss
Publisher :
ISBN 13 :
Total Pages : 262 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Adaption and Learning in Multi-agent Systems by : Gerhard Weiss

Download or read book Adaption and Learning in Multi-agent Systems written by Gerhard Weiss and published by . This book was released on 1996 with total page 262 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book is based on the workshop on Adaptation and Learning in Multi-Agent Systems, held in conjunction with the International Joint Conference on Artificial Intelligence, IJCAI'95, in Montreal, Canada in August 1995. The 14 thoroughly reviewed revised papers reflect the whole scope of current aspects in the field: they describe and analyze, both experimentally and theoretically, new learning and adaption approaches for situations in which several agents have to cooperate or compete. Also included, and aimed at the novice reader, are a comprehensive introductory survey on the area with 154 references listed and a subject index. As the first book solely devoted to this area, this volume documents the state of the art and is thus indispensable for anyone active or interested in the field."--PUBLISHER'S WEBSITE.

Encyclopedia of the Sciences of Learning

Author : Norbert M. Seel
Publisher : Springer Science & Business Media
ISBN 13 : 1441914277
Total Pages : 3643 pages
Book Rating : 4.4/5 (419 download)

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Book Synopsis Encyclopedia of the Sciences of Learning by : Norbert M. Seel

Download or read book Encyclopedia of the Sciences of Learning written by Norbert M. Seel and published by Springer Science & Business Media. This book was released on 2011-10-05 with total page 3643 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the past century, educational psychologists and researchers have posited many theories to explain how individuals learn, i.e. how they acquire, organize and deploy knowledge and skills. The 20th century can be considered the century of psychology on learning and related fields of interest (such as motivation, cognition, metacognition etc.) and it is fascinating to see the various mainstreams of learning, remembered and forgotten over the 20th century and note that basic assumptions of early theories survived several paradigm shifts of psychology and epistemology. Beyond folk psychology and its naïve theories of learning, psychological learning theories can be grouped into some basic categories, such as behaviorist learning theories, connectionist learning theories, cognitive learning theories, constructivist learning theories, and social learning theories. Learning theories are not limited to psychology and related fields of interest but rather we can find the topic of learning in various disciplines, such as philosophy and epistemology, education, information science, biology, and – as a result of the emergence of computer technologies – especially also in the field of computer sciences and artificial intelligence. As a consequence, machine learning struck a chord in the 1980s and became an important field of the learning sciences in general. As the learning sciences became more specialized and complex, the various fields of interest were widely spread and separated from each other; as a consequence, even presently, there is no comprehensive overview of the sciences of learning or the central theoretical concepts and vocabulary on which researchers rely. The Encyclopedia of the Sciences of Learning provides an up-to-date, broad and authoritative coverage of the specific terms mostly used in the sciences of learning and its related fields, including relevant areas of instruction, pedagogy, cognitive sciences, and especially machine learning and knowledge engineering. This modern compendium will be an indispensable source of information for scientists, educators, engineers, and technical staff active in all fields of learning. More specifically, the Encyclopedia provides fast access to the most relevant theoretical terms provides up-to-date, broad and authoritative coverage of the most important theories within the various fields of the learning sciences and adjacent sciences and communication technologies; supplies clear and precise explanations of the theoretical terms, cross-references to related entries and up-to-date references to important research and publications. The Encyclopedia also contains biographical entries of individuals who have substantially contributed to the sciences of learning; the entries are written by a distinguished panel of researchers in the various fields of the learning sciences.

Goal-driven Learning

Author : Ashwin Ram
Publisher : MIT Press
ISBN 13 : 9780262181655
Total Pages : 548 pages
Book Rating : 4.1/5 (816 download)

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Book Synopsis Goal-driven Learning by : Ashwin Ram

Download or read book Goal-driven Learning written by Ashwin Ram and published by MIT Press. This book was released on 1995 with total page 548 pages. Available in PDF, EPUB and Kindle. Book excerpt: Brings together a diversity of research on goal-driven learning to establish a broad, interdisciplinary framework that describes the goal-driven learning process. In cognitive science, artificial intelligence, psychology, and education, a growing body of research supports the view that the learning process is strongly influenced by the learner's goals. The fundamental tenet of goal-driven learning is that learning is largely an active and strategic process in which the learner, human or machine, attempts to identify and satisfy its information needs in the context of its tasks and goals, its prior knowledge, its capabilities, and environmental opportunities for learning. This book brings together a diversity of research on goal-driven learning to establish a broad, interdisciplinary framework that describes the goal-driven learning process. It collects and solidifies existing results on this important issue in machine and human learning and presents a theoretical framework for future investigations. The book opens with an an overview of goal-driven learning research and computational and cognitive models of the goal-driven learning process. This introduction is followed by a collection of fourteen recent research articles addressing fundamental issues of the field, including psychological and functional arguments for modeling learning as a deliberative, planful process; experimental evaluation of the benefits of utility-based analysis to guide decisions about what to learn; case studies of computational models in which learning is driven by reasoning about learning goals; psychological evidence for human goal-driven learning; and the ramifications of goal-driven learning in educational contexts. The second part of the book presents six position papers reflecting ongoing research and current issues in goal-driven learning. Issues discussed include methods for pursuing psychological studies of goal-driven learning, frameworks for the design of active and multistrategy learning systems, and methods for selecting and balancing the goals that drive learning. A Bradford Book

Machine Learning and Its Applications

Author : Georgios Paliouras
Publisher : Springer
ISBN 13 : 3540446737
Total Pages : 334 pages
Book Rating : 4.5/5 (44 download)

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Book Synopsis Machine Learning and Its Applications by : Georgios Paliouras

Download or read book Machine Learning and Its Applications written by Georgios Paliouras and published by Springer. This book was released on 2003-06-29 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent years machine learning has made its way from artificial intelligence into areas of administration, commerce, and industry. Data mining is perhaps the most widely known demonstration of this migration, complemented by less publicized applications of machine learning like adaptive systems in industry, financial prediction, medical diagnosis and the construction of user profiles for Web browsers. This book presents the capabilities of machine learning methods and ideas on how these methods could be used to solve real-world problems. The first ten chapters assess the current state of the art of machine learning, from symbolic concept learning and conceptual clustering to case-based reasoning, neural networks, and genetic algorithms. The second part introduces the reader to innovative applications of ML techniques in fields such as data mining, knowledge discovery, human language technology, user modeling, data analysis, discovery science, agent technology, finance, etc.

Understanding Language Understanding

Author : Ashwin Ram
Publisher : MIT Press
ISBN 13 : 9780262181921
Total Pages : 524 pages
Book Rating : 4.1/5 (819 download)

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Book Synopsis Understanding Language Understanding by : Ashwin Ram

Download or read book Understanding Language Understanding written by Ashwin Ram and published by MIT Press. This book was released on 1999 with total page 524 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book highlights cutting-edge research relevant to the building of a computational model of reading comprehension, as in the processing and understanding of a natural language text or story. The book takes an interdisciplinary approach to the study of reading, with contributions from computer science, psychology, and philosophy. Contributors cover the theoretical and psychological foundations of the research in discussions of what it means to understand a text, how one builds a computational model, and related issues in knowledge representation and reasoning. The book also addresses some of the broader issues that a natural language system must deal with, such as reading in context, linguistic novelty, and information extraction.

Machine Learning

Author : Yves Kodratoff
Publisher : Elsevier
ISBN 13 : 0080510558
Total Pages : 836 pages
Book Rating : 4.0/5 (85 download)

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Book Synopsis Machine Learning by : Yves Kodratoff

Download or read book Machine Learning written by Yves Kodratoff and published by Elsevier. This book was released on 2014-06-28 with total page 836 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Learning: An Artificial Intelligence Approach, Volume III presents a sample of machine learning research representative of the period between 1986 and 1989. The book is organized into six parts. Part One introduces some general issues in the field of machine learning. Part Two presents some new developments in the area of empirical learning methods, such as flexible learning concepts, the Protos learning apprentice system, and the WITT system, which implements a form of conceptual clustering. Part Three gives an account of various analytical learning methods and how analytic learning can be applied to various specific problems. Part Four describes efforts to integrate different learning strategies. These include the UNIMEM system, which empirically discovers similarities among examples; and the DISCIPLE multistrategy system, which is capable of learning with imperfect background knowledge. Part Five provides an overview of research in the area of subsymbolic learning methods. Part Six presents two types of formal approaches to machine learning. The first is an improvement over Mitchell's version space method; the second technique deals with the learning problem faced by a robot in an unfamiliar, deterministic, finite-state environment.

Proceedings of the Third International Workshop on Multistrategy Learning

Author : International Workshop on Multistrategy Learning
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (245 download)

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Book Synopsis Proceedings of the Third International Workshop on Multistrategy Learning by : International Workshop on Multistrategy Learning

Download or read book Proceedings of the Third International Workshop on Multistrategy Learning written by International Workshop on Multistrategy Learning and published by . This book was released on 1996 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Development of Knowledge-Based Systems for Engineering

Author : Carlo Tasso
Publisher : Springer
ISBN 13 : 370912784X
Total Pages : 241 pages
Book Rating : 4.7/5 (91 download)

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Book Synopsis Development of Knowledge-Based Systems for Engineering by : Carlo Tasso

Download or read book Development of Knowledge-Based Systems for Engineering written by Carlo Tasso and published by Springer. This book was released on 2014-05-04 with total page 241 pages. Available in PDF, EPUB and Kindle. Book excerpt: The goal of the volume is twofold: to help engineers to understand the design and development process and the specific techniques utilized for constructing expert systems in engineering and, secondly, to introduce computer specialists to significant applications of knowledge-based techniques in engineering. Among the authors are world famous experts of engineering and knowledge-based systems development.

Building Intelligent Agents

Author : Gheorghe Tecuci
Publisher : Morgan Kaufmann
ISBN 13 : 9780126851250
Total Pages : 356 pages
Book Rating : 4.8/5 (512 download)

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Book Synopsis Building Intelligent Agents by : Gheorghe Tecuci

Download or read book Building Intelligent Agents written by Gheorghe Tecuci and published by Morgan Kaufmann. This book was released on 1998-06-23 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt: Building Intelligent Agents is unique in its comprehensive coverage of the subject. The first part of the book presents an original theory for building intelligent agents and a methodology and tool that implement the theory. The second part of the book presents complex and detailed case studies of building different types of agents: an educational assessment agent, a statistical analysis assessment and support agent, an engineering design assistant, and a virtual military commander. Also featured in this book is Disciple, a toolkit for building interactive agents which function in much the same way as a human apprentice. Disciple-based agents can reason both with incomplete information, but also with information that is potentially incorrect. This approach, in which the agent learns its behavior from its teacher, integrates many machine learning and knowledge acquisition techniques, taking advantage of their complementary strengths to compensate for each others weakness. As a consequence, it significantly reduces (or even eliminates) the involvement of a knowledge engineer in the process of building an intelligent agent.

Metareasoning

Author : Michael T. Cox
Publisher : MIT Press
ISBN 13 : 0262014807
Total Pages : 349 pages
Book Rating : 4.2/5 (62 download)

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Book Synopsis Metareasoning by : Michael T. Cox

Download or read book Metareasoning written by Michael T. Cox and published by MIT Press. This book was released on 2011 with total page 349 pages. Available in PDF, EPUB and Kindle. Book excerpt: Experts report on the latest artificial intelligence research concerning reasoning about reasoning itself.

Case-Based Reasoning Research and Development

Author : David B. Leake
Publisher : Springer Science & Business Media
ISBN 13 : 9783540632337
Total Pages : 668 pages
Book Rating : 4.6/5 (323 download)

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Book Synopsis Case-Based Reasoning Research and Development by : David B. Leake

Download or read book Case-Based Reasoning Research and Development written by David B. Leake and published by Springer Science & Business Media. This book was released on 1997-07-09 with total page 668 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the Second International Conference on Case-Based Reasoning, ICCBR-97, held in Providence, RI, USA, in July 1997. The volume presents 39 revised full scientific papers selected from a total of 102 submissions; also included are 20 revised application papers. Among the topics covered are representation and formalization, indexing and retrieval, adaptation, learning, integrated approaches, creative reasoning, CBR and uncertainty. This collection of papers is a comprehensive documentation of the state of the art in CBR research and development.

Web Usage Analysis and User Profiling

Author : Brij Masand
Publisher : Springer Science & Business Media
ISBN 13 : 3540678182
Total Pages : 190 pages
Book Rating : 4.5/5 (46 download)

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Book Synopsis Web Usage Analysis and User Profiling by : Brij Masand

Download or read book Web Usage Analysis and User Profiling written by Brij Masand and published by Springer Science & Business Media. This book was released on 2000-07-26 with total page 190 pages. Available in PDF, EPUB and Kindle. Book excerpt: After the advent of data mining and its successful application on conventional data, Web-related information has been an appropriate and increasingly popular target of knowledge discovery. Depending on whether the data used in the knowledge discovery process concerns the Web itself in terms of content or the usage of the content, one distinguishes between Web content mining and Web usage mining. This book is the first one entirely devoted to Web usage mining. It originates from the WEBKDD'99 Workshop held during the 1999 KDD Conference. The ten revised full papers presented together with an introductory survey by the volume editors documents the state of the art in this exciting new area. The book presents topical sections on Modeling the User, Discovering Rules and Patterns of Navigation, and Measuring interestingness in Web Usage Mining.