Download or read book Using Meta level Inference to Constrain Search and to Learn Strategies in Equation Solving written by Bernard Silver and published by . This book was released on 1984 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Using Meta level Inference to Constrain Search and to Learn Strategies in Equation Solving written by Bernard Silver and published by . This book was released on 1984 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
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 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 Machine Learning written by Tom M. Mitchell and published by Springer Science & Business Media. This book was released on 1986-04-30 with total page 460 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 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 Ryszard Stanisław Michalski and published by Morgan Kaufmann. This book was released on 1983 with total page 758 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Machine Learning of Robot Assembly Plans written by Alberto Maria Segre and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 244 pages. Available in PDF, EPUB and Kindle. Book excerpt: The study of artificial intelligence (AI) is indeed a strange pursuit. Unlike most other disciplines, few AI researchers even agree on a mutually acceptable definition of their chosen field of study. Some see AI as a sub field of computer science, others see AI as a computationally oriented branch of psychology or linguistics, while still others see it as a bag of tricks to be applied to an entire spectrum of diverse domains. This lack of unified purpose among the AI community makes this a very exciting time for AI research: new and diverse projects are springing up literally every day. As one might imagine, however, this diversity also leads to genuine difficulties in assessing the significance and validity of AI research. These difficulties are an indication that AI has not yet matured as a science: it is still at the point where people are attempting to lay down (hopefully sound) foundations. Ritchie and Hanna [1] posit the following categorization as an aid in assessing the validity of an AI research endeavor: (1) The project could introduce, in outline, a novel (or partly novel) idea or set of ideas. (2) The project could elaborate the details of some approach. Starting with the kind of idea in (1), the research could criticize it or fill in further details (3) The project could be an AI experiment, where a theory as in (1) and (2) is applied to some domain. Such experiments are usually computer programs that implement a particular theory.
Download or read book Exploring Artificial Intelligence written by Howard E. Shrobe and published by Morgan Kaufmann. This book was released on 2014-05-12 with total page 720 pages. Available in PDF, EPUB and Kindle. Book excerpt: Exploring Artificial Intelligence: Survey Talks from the National Conference on Artificial Intelligence provides information pertinent to the distinct subareas of artificial intelligence research. This book discusses developments in machine learning techniques. Organized into six parts encompassing 16 chapters, this book begins with an overview of intelligent tutoring systems, which describes how to guide a student to learn new concepts. This text then links closely with one of the concerns of intelligent tutoring systems, namely how to interact through the utilization of natural language. Other chapters consider the various aspects of natural language understanding and survey the huge body of work that tries to characterize heuristic search programs. This book discusses as well how computer programs can create plans to satisfy goals. The final chapter deals with computational facilities that support. This book is a valuable resource for cognitive scientists, psychologists, domain experts, computer scientists, instructional designers, expert teachers, and research workers.
Download or read book Cognitive Science and Mathematics Education written by Alan H. Schoenfeld and published by Routledge. This book was released on 2013-04-03 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume is a result of mathematicians, cognitive scientists, mathematics educators, and classroom teachers combining their efforts to help address issues of importance to classroom instruction in mathematics. In so doing, the contributors provide a general introduction to fundamental ideas in cognitive science, plus an overview of cognitive theory and its direct implications for mathematics education. A practical, no-nonsense attempt to bring recent research within reach for practicing teachers, this book also raises many issues for cognitive researchers to consider.
Download or read book Meta level Inference written by Bernard Silver and published by North Holland. This book was released on 1986 with total page 250 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Machine and Human Learning written by Yves Kodratoff and published by . This book was released on 1989 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Computers and Mathematics written by David Alexander Smith and published by MAA Press. This book was released on 1988 with total page 164 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Proceedings of the International Workshop on Machine Learning written by and published by . This book was released on 1985 with total page 270 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Logic Programming written by I. Balbin and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 370 pages. Available in PDF, EPUB and Kindle. Book excerpt: Logic Programming was effectively defined as a discipline in the early seventies. It is only during the early to mid eighties that books, conferences and journals devoted entirely to Logic Programming began to appear. Consequently, much of the work done during this first crucial decade in Marseilles, Edinburgh, London, Budapest and Stockholm (to name a few) is often overlooked or difficult to trace. There are now two main regular conferences on Logic Programming, and at least five journals: The Journal of Logic Programming, New Generation Computing, Automated Reasoning, The Journal of SJmbolic Computation, and Future Generation Computer Systems. Logic Programming, however, has its roots in Automated Theorem Proving and via the expanding area of expert systems, strongly influences researchers in such varied fields as Civil Engineering, Chemistry, Law, etc. Consequently, many papers related to Logic Programming appear in a wide variety of journals and proceedings of conferences in other disciplines. This is particularly true of Computer Science where a revolution is taking place in hardware design, programming languages, and more recently databases. One cannot overestimate the importance of such a bibliography.
Download or read book Index to Theses Accepted for Higher Degrees by the Universities of Great Britain and Ireland and the Council for National Academic Awards written by and published by . This book was released on 1985 with total page 398 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book British Reports Translations and Theses written by British Library. Lending Division and published by . This book was released on 1984 with total page 444 pages. Available in PDF, EPUB and Kindle. Book excerpt: Issue for Mar. 1981 contains index for Jan.-Mar. 1981 in microfiche form.
