Learning Search Control Knowledge PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Learning Search Control Knowledge PDF full book. Access full book title Learning Search Control Knowledge by Steven Minton. Download full books in PDF and EPUB format.
Author: Steven Minton
Publisher: Springer Science & Business Media
ISBN: 1461317037
Category : Computers
Languages : en
Pages : 217
Get Book Here
Book Description
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.
Author: Steven Minton
Publisher: Springer Science & Business Media
ISBN: 1461317037
Category : Computers
Languages : en
Pages : 217
Get Book Here
Book Description
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.
Author: Ioannis Vlahavas
Publisher: IGI Global
ISBN: 1591404525
Category : Computers
Languages : en
Pages : 364
Get Book Here
Book Description
The Intelligent Techniques for Planning presents a number of modern approaches to the area of automated planning. These approaches combine methods from classical planning such as the construction of graphs and the use of domain-independent heuristics with techniques from other areas of artificial intelligence. This book discuses, in detail, a number of state-of-the-art planning systems that utilize constraint satisfaction techniques in order to deal with time and resources, machine learning in order to utilize experience drawn from past runs, methods from knowledge systems for more expressive representation of knowledge and ideas from other areas such as Intelligent Agents. Apart from the thorough analysis and implementation details, each chapter of the book also provides extensive background information about its subject and presents and comments on similar approaches done in the past.
Author: Malik Ghallab
Publisher:
ISBN: 9784274900648
Category : Artificial intelligence
Languages : en
Pages : 422
Get Book Here
Book Description
Author: International Joint Conferences on Artificial Intelligence
Publisher: Morgan Kaufmann
ISBN: 9781558604803
Category : Artificial intelligence
Languages : en
Pages : 1720
Get Book Here
Book Description
Author: David W. Aha
Publisher: Springer Science & Business Media
ISBN: 9401720533
Category : Computers
Languages : en
Pages : 421
Get Book Here
Book Description
This edited collection describes recent progress on lazy learning, a branch of machine learning concerning algorithms that defer the processing of their inputs, reply to information requests by combining stored data, and typically discard constructed replies. It is the first edited volume in AI on this topic, whose many synonyms include `instance-based', `memory-based'. `exemplar-based', and `local learning', and whose topic intersects case-based reasoning and edited k-nearest neighbor classifiers. It is intended for AI researchers and students interested in pursuing recent progress in this branch of machine learning, but, due to the breadth of its contributions, it should also interest researchers and practitioners of data mining, case-based reasoning, statistics, and pattern recognition.
Author: Howard J. Hamilton
Publisher: Springer
ISBN: 3540454861
Category : Computers
Languages : en
Pages : 462
Get Book Here
Book Description
This book constitutes the refereed proceedings of the 13th Biennial Conference of the Canadian Society for Computational Studies of Intelligence, AI 2000, held in Montreal, Quebec, Canada, in May 2000. The 25 revised full papers presented together with 12 10-page posters were carefully reviewed and selected from more than 70 submissions. The papers are organized in topical sections on games and constraint satisfaction; natural language processing; knowledge representation; AI applications; machine learning and data mining; planning, theorem proving, and artificial life; and neural networks.
Author: Lorenza Saitta
Publisher: Morgan Kaufmann Publishers
ISBN:
Category : Computers
Languages : en
Pages : 580
Get Book Here
Book Description
Author: Eugene Fink
Publisher: Physica
ISBN: 3790817740
Category : Computers
Languages : en
Pages : 360
Get Book Here
Book Description
The purpose of our research is to enhance the efficiency of AI problem solvers by automating representation changes. We have developed a system that improves the description of input problems and selects an appropriate search algorithm for each given problem. Motivation. Researchers have accumulated much evidence on the impor tance of appropriate representations for the efficiency of AI systems. The same problem may be easy or difficult, depending on the way we describe it and on the search algorithm we use. Previous work on the automatic im provement of problem descriptions has mostly been limited to the design of individual learning algorithms. The user has traditionally been responsible for the choice of algorithms appropriate for a given problem. We present a system that integrates multiple description-changing and problem-solving algorithms. The purpose of the reported work is to formalize the concept of representation and to confirm the following hypothesis: An effective representation-changing system can be built from three parts: • a library of problem-solving algorithms; • a library of algorithms that improve problem descriptions; • a control module that selects algorithms for each given problem.
Author: Malik Ghallab
Publisher: Elsevier
ISBN: 1558608567
Category : Business & Economics
Languages : en
Pages : 665
Get Book Here
Book Description
Publisher Description
Author:
Publisher:
ISBN:
Category : Artificial intelligence
Languages : en
Pages : 576
Get Book Here
Book Description
