Download or read book Investigating Explanation Based Learning written by Gerald DeJong and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 447 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explanation-Based Learning (EBL) can generally be viewed as substituting background knowledge for the large training set of exemplars needed by conventional or empirical machine learning systems. The background knowledge is used automatically to construct an explanation of a few training exemplars. The learned concept is generalized directly from this explanation. The first EBL systems of the modern era were Mitchell's LEX2, Silver's LP, and De Jong's KIDNAP natural language system. Two of these systems, Mitchell's and De Jong's, have led to extensive follow-up research in EBL. This book outlines the significant steps in EBL research of the Illinois group under De Jong. This volume describes theoretical research and computer systems that use a broad range of formalisms: schemas, production systems, qualitative reasoning models, non-monotonic logic, situation calculus, and some home-grown ad hoc representations. This has been done consciously to avoid sacrificing the ultimate research significance in favor of the expediency of any particular formalism. The ultimate goal, of course, is to adopt (or devise) the right formalism.

Download or read book Extending Explanation Based Learning by Generalizing the Structure of Explanations written by Jude W. Shavlik and published by Morgan Kaufmann. This book was released on 2014-07-10 with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt: Extending Explanation-Based Learning by Generalizing the Structure of Explanations presents several fully-implemented computer systems that reflect theories of how to extend an interesting subfield of machine learning called explanation-based learning. This book discusses the need for generalizing explanation structures, relevance to research areas outside machine learning, and schema-based problem solving. The result of standard explanation-based learning, BAGGER generalization algorithm, and empirical analysis of explanation-based learning are also elaborated. This text likewise covers the effect of increased problem complexity, rule access strategies, empirical study of BAGGER2, and related work in similarity-based learning. This publication is suitable for readers interested in machine learning, especially explanation-based learning.

Download or read book Explanation Based Neural Network Learning written by Sebastian Thrun and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt: Lifelong learning addresses situations in which a learner faces a series of different learning tasks providing the opportunity for synergy among them. Explanation-based neural network learning (EBNN) is a machine learning algorithm that transfers knowledge across multiple learning tasks. When faced with a new learning task, EBNN exploits domain knowledge accumulated in previous learning tasks to guide generalization in the new one. As a result, EBNN generalizes more accurately from less data than comparable methods. Explanation-Based Neural Network Learning: A Lifelong Learning Approach describes the basic EBNN paradigm and investigates it in the context of supervised learning, reinforcement learning, robotics, and chess. `The paradigm of lifelong learning - using earlier learned knowledge to improve subsequent learning - is a promising direction for a new generation of machine learning algorithms. Given the need for more accurate learning methods, it is difficult to imagine a future for machine learning that does not include this paradigm.' From the Foreword by Tom M. Mitchell.

Download or read book Machine Learning written by Tom M. Mitchell and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 413 pages. Available in PDF, EPUB and Kindle. Book excerpt: One of the currently most active research areas within Artificial Intelligence is the field of Machine Learning. which involves the study and development of computational models of learning processes. A major goal of research in this field is to build computers capable of improving their performance with practice and of acquiring knowledge on their own. The intent of this book is to provide a snapshot of this field through a broad. representative set of easily assimilated short papers. As such. this book is intended to complement the two volumes of Machine Learning: An Artificial Intelligence Approach (Morgan-Kaufman Publishers). which provide a smaller number of in-depth research papers. Each of the 77 papers in the present book summarizes a current research effort. and provides references to longer expositions appearing elsewhere. These papers cover a broad range of topics. including research on analogy. conceptual clustering. explanation-based generalization. incremental learning. inductive inference. learning apprentice systems. machine discovery. theoretical models of learning. and applications of machine learning methods. A subject index IS provided to assist in locating research related to specific topics. The majority of these papers were collected from the participants at the Third International Machine Learning Workshop. held June 24-26. 1985 at Skytop Lodge. Skytop. Pennsylvania. While the list of research projects covered is not exhaustive. we believe that it provides a representative sampling of the best ongoing work in the field. and a unique perspective on where the field is and where it is headed.

Download or read book Learning to Learn written by Sebastian Thrun and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 346 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the past three decades or so, research on machine learning and data mining has led to a wide variety of algorithms that learn general functions from experience. As machine learning is maturing, it has begun to make the successful transition from academic research to various practical applications. Generic techniques such as decision trees and artificial neural networks, for example, are now being used in various commercial and industrial applications. Learning to Learn is an exciting new research direction within machine learning. Similar to traditional machine-learning algorithms, the methods described in Learning to Learn induce general functions from experience. However, the book investigates algorithms that can change the way they generalize, i.e., practice the task of learning itself, and improve on it. To illustrate the utility of learning to learn, it is worthwhile comparing machine learning with human learning. Humans encounter a continual stream of learning tasks. They do not just learn concepts or motor skills, they also learn bias, i.e., they learn how to generalize. As a result, humans are often able to generalize correctly from extremely few examples - often just a single example suffices to teach us a new thing. A deeper understanding of computer programs that improve their ability to learn can have a large practical impact on the field of machine learning and beyond. In recent years, the field has made significant progress towards a theory of learning to learn along with practical new algorithms, some of which led to impressive results in real-world applications. Learning to Learn provides a survey of some of the most exciting new research approaches, written by leading researchers in the field. Its objective is to investigate the utility and feasibility of computer programs that can learn how to learn, both from a practical and a theoretical point of view.

Download or read book Mind Matters written by David M. Steier and published by Psychology Press. This book was released on 2014-03-05 with total page 492 pages. Available in PDF, EPUB and Kindle. Book excerpt: Based on a symposium honoring the extensive work of Allen Newell -- one of the founders of artificial intelligence, cognitive science, human-computer interaction, and the systematic study of computational architectures -- this volume demonstrates how unifying themes may be found in the diversity that characterizes current research on computers and cognition. The subject matter includes: * an overview of cognitive and computer science by leading researchers in the field; * a comprehensive description of Allen Newell's "Soar" -- a computational architecture he developed as a unified theory of cognition; * commentary on how the Soar theory of cognition relates to important issues in cognitive and computer science; * rigorous treatments of controversial issues in cognition -- methodology of cognitive science, hybrid approaches to machine learning, word-sense disambiguation in understanding material language, and the role of capability processing constraints in architectural theory; * comprehensive and systematic methods for studying architectural evolution in both hardware and software; * a thorough discussion of the use of analytic models in human computer interaction; * extensive reviews of important experiments in the study of scientific discovery and deduction; and * an updated analysis of the role of symbols in information processing by Herbert Simon. Incorporating the research of top scientists inspired by Newell's work, this volume will be of strong interest to a large variety of scientific communities including psychologists, computational linguists, computer scientists and engineers, and interface designers. It will also be valuable to those who study the scientific process itself, as it chronicles the impact of Newell's approach to research, simultaneously delving into each scientific discipline and producing results that transcend the boundaries of those disciplines.

Download or read book Investigating Classroom Interaction written by and published by BRILL. This book was released on 2009-01-01 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book adds a new perspective to existing research methodology literature on analyzing social interactions in the classroom. Not only does this book introduce multiple research methodologies for analyzing classroom interactions but it also demonstrates these methodologies at work in different empirical research studies. The authors of this book are all internationally well recognized for their research work on the social life of classrooms, and now, for the first time, they provide concrete accounts of the ways in which the theories and methodologies they have chosen to guide their research work function in action. These 'black boxes’ or 'tacit knowledge' of conducting different types of analyses on classroom interaction have seldom been opened up in such a concrete way in the existing research literature. This book is an edited collection of papers introducing strands of research on classroom interaction whose logic of inquiry illuminate different approaches, analyses, and interpretations of social interactions and discourses in contemporary classroom settings. The methodological approaches discussed draw on studies of language and discourse, ethnography, as well as on sociological, psychological, and domain-specific analyses. In recognizing the complexity and challenges in mapping out the complex research territory focusing on classroom interactions, the prime goal of the book is to build a complimentary context for discussion of the ways in which different approaches to classroom interaction are realized and how they produce different analyses because of their purpose, conceptual framework, and methodological choice. The illumination of diverse approaches to classroom interaction and discourse is believed to demonstrate the potential and challenges each strand of research is likely to bring towards understanding the psychological, social and cultural life of the classroom and how these mediate the situated practice of teaching and learning in today’s schooling. This book is targeted towards researchers and graduate students working within the field of social sciences, education and psychology. It also makes an excellent text for courses in research methodology, education, and related fields.

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.

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

Download or read book Internal and External Narrative Generation Based on Post Narratology Emerging Research and Opportunities written by Ogata, Takashi and published by IGI Global. This book was released on 2020-01-03 with total page 444 pages. Available in PDF, EPUB and Kindle. Book excerpt: Narrative generation can be applied to systematic frameworks that cover theoretical and philosophical thoughts of narratives and narrative generation, analytical research of related narrative genres and narrative works, and narrative works writing and creation using narrative generation systems. The design and development of narrative generation systems refers to the themes regarding narrative work creation as arts and literature through narrative generation systems beyond narrative generation systems as a technology. Internal and External Narrative Generation Based on Post-Narratology: Emerging Research and Opportunities is an essential scholarly publication that explores the creation of narrative systems using practical frameworks and advanced narrative analysis. Highlighting a range of topics such as marketing, synthetic narrative, and application systems, this book is ideal for academicians, information technology professionals, designers, developers, researchers, and students.

Download or read book Machine Learning ECML 95 written by Nada Lavrač and published by Springer Science & Business Media. This book was released on 1995-04-05 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume constitutes the proceedings of the Eighth European Conference on Machine Learning ECML-95, held in Heraclion, Crete in April 1995. Besides four invited papers the volume presents revised versions of 14 long papers and 26 short papers selected from a total of 104 submissions. The papers address all current aspects in the area of machine learning; also logic programming, planning, reasoning, and algorithmic issues are touched upon.

Download or read book Data Mining Using Grammar Based Genetic Programming and Applications written by Man Leung Wong and published by Springer Science & Business Media. This book was released on 2005-12-02 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data mining involves the non-trivial extraction of implicit, previously unknown, and potentially useful information from databases. Genetic Programming (GP) and Inductive Logic Programming (ILP) are two of the approaches for data mining. This book first sets the necessary backgrounds for the reader, including an overview of data mining, evolutionary algorithms and inductive logic programming. It then describes a framework, called GGP (Generic Genetic Programming), that integrates GP and ILP based on a formalism of logic grammars. The formalism is powerful enough to represent context- sensitive information and domain-dependent knowledge. This knowledge can be used to accelerate the learning speed and/or improve the quality of the knowledge induced. A grammar-based genetic programming system called LOGENPRO (The LOGic grammar based GENetic PROgramming system) is detailed and tested on many problems in data mining. It is found that LOGENPRO outperforms some ILP systems. We have also illustrated how to apply LOGENPRO to emulate Automatically Defined Functions (ADFs) to discover problem representation primitives automatically. By employing various knowledge about the problem being solved, LOGENPRO can find a solution much faster than ADFs and the computation required by LOGENPRO is much smaller than that of ADFs. Moreover, LOGENPRO can emulate the effects of Strongly Type Genetic Programming and ADFs simultaneously and effortlessly. Data Mining Using Grammar Based Genetic Programming and Applications is appropriate for researchers, practitioners and clinicians interested in genetic programming, data mining, and the extraction of data from databases.

Download or read book Machine Learning Proceedings 1989 written by Machine Learning and published by Morgan Kaufmann. This book was released on 2016-04-20 with total page 510 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Learning Proceedings 1989

Download or read book Machine Learning Proceedings 1990 written by Machine Learning and published by Morgan Kaufmann. This book was released on 2014-05-23 with total page 427 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Learning Proceedings 1990

Download or read book The Wiley Blackwell Handbook of Childhood Cognitive Development written by Usha Goswami and published by John Wiley & Sons. This book was released on 2013-11-11 with total page 818 pages. Available in PDF, EPUB and Kindle. Book excerpt: This definitive volume is the result of collaboration by top scholars in the field of children's cognition. New edition offers an up-to-date overview of all the major areas of importance in the field, and includes new data from cognitive neuroscience and new chapters on social cognitive development and language Provides state-of-the-art summaries of current research by international specialists in different areas of cognitive development Spans aspects of cognitive development from infancy to the onset of adolescence Includes chapters on symbolic reasoning, pretend play, spatial development, abnormal cognitive development and current theoretical perspectives

Download or read book Readings in Machine Learning written by Jude W. Shavlik and published by Morgan Kaufmann. This book was released on 1990 with total page 868 pages. Available in PDF, EPUB and Kindle. Book excerpt: The ability to learn is a fundamental characteristic of intelligent behavior. Consequently, machine learning has been a focus of artificial intelligence since the beginnings of AI in the 1950s. The 1980s saw tremendous growth in the field, and this growth promises to continue with valuable contributions to science, engineering, and business. Readings in Machine Learning collects the best of the published machine learning literature, including papers that address a wide range of learning tasks, and that introduce a variety of techniques for giving machines the ability to learn. The editors, in cooperation with a group of expert referees, have chosen important papers that empirically study, theoretically analyze, or psychologically justify machine learning algorithms. The papers are grouped into a dozen categories, each of which is introduced by the editors.

Download or read book Toward an Integrated Approach to Narrative Generation Emerging Research and Opportunities written by Ogata, Takashi and published by IGI Global. This book was released on 2019-10-25 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt: The concept of narrative has exerted a strong influence on a wide range of fields, from the humanities such as literature (and art and entertainment) to social studies, psychiatry, and psychology. The framework that allows access to narratives across a wide range of areas, from science to the humanities, has the potential to be improved as a fusion of cognitive science and artificial intelligence. Toward an Integrated Approach to Narrative Generation: Emerging Research and Opportunities is a critical scholarly book that focuses on the significance of narratives and narrative generation in various aspects of human society. Featuring an array of topics such as philosophy, narratology, and advertising, this book is ideal for software developers, academicians, philosophy professionals, researchers, and students in the fields of cognitive studies, literary studies, and digital content design and development.