Download or read book Learning Search Control Knowledge written by Steven Minton and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 217 pages. Available in PDF, EPUB and Kindle. Book excerpt: The ability to learn from experience is a fundamental requirement for intelligence. One of the most basic characteristics of human intelligence is that people can learn from problem solving, so that they become more adept at solving problems in a given domain as they gain experience. This book investigates how computers may be programmed so that they too can learn from experience. Specifically, the aim is to take a very general, but inefficient, problem solving system and train it on a set of problems from a given domain, so that it can transform itself into a specialized, efficient problem solver for that domain. on a knowledge-intensive Recently there has been considerable progress made learning approach, explanation-based learning (EBL), that brings us closer to this possibility. As demonstrated in this book, EBL can be used to analyze a problem solving episode in order to acquire control knowledge. Control knowledge guides the problem solver's search by indicating the best alternatives to pursue at each choice point. An EBL system can produce domain specific control knowledge by explaining why the choices made during a problem solving episode were, or were not, appropriate.

Download or read book Learning Search Control Knowledge for Equational Deduction written by S. A. Schulz and published by IOS Press. This book was released on 2000 with total page 204 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis presents an approach to learning good search guiding heuristics for the supposition-based theorom prover E in equational deductions. Search decisions from successful proof searches are represented as sets annotated clause patterns. Term Space Mapping, an alternative learning method for recursive structures is used to learn heuristic evaluation functions for the evaluation of potential new consequences. Experimental results with extended system E/TSM show the success of the approach. Additional contributions of the thesis are an extended superposition calculus and a description of both the proof procedure and the implementation of a state-of-the-art equational theorem prover.

Download or read book Learning Search Control Knowledge for the Deep Space Network Scheduling Problem written by Jonathan Matthew Gratch and published by . This book was released on 1993 with total page 36 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book LEARNING SEARCH CONTROL KNOWLEDGE FOR PLANNING WITH CONJUNCTIVE GOALS written by KWANG RYEL RYU and published by . This book was released on 1992 with total page 428 pages. Available in PDF, EPUB and Kindle. Book excerpt: learning correct rules. The overhead involved in learning is very low because this methodology needs only a small amount of data to learn from, namely, the goal stacks from the leaf nodes of a failure search tree, rather than the whole search tree. Empirical tests show that the rules derived by our system PAL, after sufficient learning, performs as well as, and in some cases better than, those derived by other systems such as PRODIGY/EBL and STATIC.

Download or read book Foundations of Knowledge Acquisition written by Susan Chipman and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 347 pages. Available in PDF, EPUB and Kindle. Book excerpt: One of the most intriguing questions about the new computer technology that has appeared over the past few decades is whether we humans will ever be able to make computers learn. As is painfully obvious to even the most casual computer user, most current computers do not. Yet if we could devise learning techniques that enable computers to routinely improve their performance through experience, the impact would be enormous. The result would be an explosion of new computer applications that would suddenly become economically feasible (e. g. , personalized computer assistants that automatically tune themselves to the needs of individual users), and a dramatic improvement in the quality of current computer applications (e. g. , imagine an airline scheduling program that improves its scheduling method based on analyzing past delays). And while the potential economic impact ofsuccessful learning methods is sufficient reason to invest in research into machine learning, there is a second significant reason: studying machine learning helps us understand our own human learning abilities and disabilities, leading to the possibility of improved methods in education. While many open questions remain aboutthe methods by which machines and humans might learn, significant progress has been made.

Download or read book Encyclopedia of Artificial Intelligence written by Juan Ramon Rabunal and published by IGI Global. This book was released on 2009-01-01 with total page 1640 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book is a comprehensive and in-depth reference to the most recent developments in the field covering theoretical developments, techniques, technologies, among others"--Provided by publisher.

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 1991 written by Machine Learning and published by Morgan Kaufmann. This book was released on 2014-06-28 with total page 661 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine 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 Handbook of Research on Machine Learning Applications and Trends Algorithms Methods and Techniques written by Olivas, Emilio Soria and published by IGI Global. This book was released on 2009-08-31 with total page 852 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book investiges machine learning (ML), one of the most fruitful fields of current research, both in the proposal of new techniques and theoretic algorithms and in their application to real-life problems"--Provided by publisher.

Download or read book Machine Learning written by Mr. Y. David Solomon Raju, M. Tech, (Ph. D.), LMISTE, LMISOI, FIETE, MIE, MIAENG, Associate Professor, Department of Electronics and Communication Engineering, Holy Mary Institute of Technology & Science (AUTONOMOUS) and published by GCS PUBLISHERS. This book was released on with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Learning WRITTEN BY Y. David Solomon Raju, K. Shyamala, Ch. Sumalatha

Download or read book Foundations of Knowledge Acquisition Machine learning written by Susan F. Chipman and published by . This book was released on 1993 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Planning and Learning by Analogical Reasoning written by Manuela M. Veloso and published by Springer Science & Business Media. This book was released on 1994-12-07 with total page 204 pages. Available in PDF, EPUB and Kindle. Book excerpt: This research monograph describes the integration of analogical and case-based reasoning into general problem solving and planning as a method of speedup learning. The method, based on derivational analogy, has been fully implemented in PRODIGY/ANALOGY and proven in practice to be amenable to scaling up, both in terms of domain and problem complexity. In this work, the strategy-level learning process is cast for the first time as the automation of the complete cycle of construction, storing, retrieving, and flexibly reusing problem solving experience. The algorithms involved are presented in detail and numerous examples are given. Thus the book addresses researchers as well as practitioners.

Download or read book Machine Learning Methods for Planning written by Steven Minton and published by Morgan Kaufmann. This book was released on 2014-05-12 with total page 555 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Learning Methods for Planning provides information pertinent to learning methods for planning and scheduling. This book covers a wide variety of learning methods and learning architectures, including analogical, case-based, decision-tree, explanation-based, and reinforcement learning. Organized into 15 chapters, this book begins with an overview of planning and scheduling and describes some representative learning systems that have been developed for these tasks. This text then describes a learning apprentice for calendar management. Other chapters consider the problem of temporal credit assignment and describe tractable classes of problems for which optimal plans can be derived. This book discusses as well how reactive, integrated systems give rise to new requirements and opportunities for machine learning. The final chapter deals with a method for learning problem decompositions, which is based on an idealized model of efficiency for problem-reduction search. This book is a valuable resource for production managers, planners, scientists, and research workers.

Download or read book A Framework for Evaluating Search Control Strategies written by Jonathan Matthew Gratch and published by . This book was released on 1990 with total page 32 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book KI 2001 Advances in Artificial Intelligence written by Franz Baader and published by Springer Science & Business Media. This book was released on 2001-09-05 with total page 484 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the Joint German/Austrian Conference on Artificial Intelligence, KI 2001, held in Vienna, Austria in September 2001. The 29 revised full technical papers presented together with one invited paper and four posters of industrial papers were carefully reviewed and selected from 79 submissions. All current aspects in AI are addressed, ranging from theoretical and foundational issues to industrial applications.

Download or read book Logics and Type Systems in Theory and Practice written by Venanzio Capretta and published by Springer Nature. This book was released on with total page 284 pages. Available in PDF, EPUB and Kindle. Book excerpt: