Machine Learning, Meta-Reasoning and Logics

Machine Learning, Meta-Reasoning and Logics

Author: Pavel B. Brazdil

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 339

ISBN-13: 1461316413

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This book contains a selection of papers presented at the International Workshop Machine Learning, Meta-Reasoning and Logics held in Hotel de Mar in Sesimbra, Portugal, 15-17 February 1988. All the papers were edited afterwards. The Workshop encompassed several fields of Artificial Intelligence: Machine Learning, Belief Revision, Meta-Reasoning and Logics. The objective of this Workshop was not only to address the common issues in these areas, but also to examine how to elaborate cognitive architectures for systems capable of learning from experience, revising their beliefs and reasoning about what they know. Acknowledgements The editing of this book has been supported by COST-13 Project Machine Learning and Knowledge Acquisition funded by the Commission o/the European Communities which has covered a substantial part of the costs. Other sponsors who have supported this work were Junta Nacional de lnvestiga~ao Cientlfica (JNICT), lnstituto Nacional de lnvestiga~ao Cientlfica (INIC), Funda~ao Calouste Gulbenkian. I wish to express my gratitude to all these institutions. Finally my special thanks to Paula Pereira and AnaN ogueira for their help in preparing this volume. This work included retyping all the texts and preparing the camera-ready copy. Introduction 1 1. Meta-Reasoning and Machine Learning The first chapter is concerned with the role meta-reasoning plays in intelligent systems capable of learning. As we can see from the papers that appear in this chapter, there are basically two different schools of thought.


Book Synopsis Machine Learning, Meta-Reasoning and Logics by : Pavel B. Brazdil

Download or read book Machine Learning, Meta-Reasoning and Logics written by Pavel B. Brazdil and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 339 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains a selection of papers presented at the International Workshop Machine Learning, Meta-Reasoning and Logics held in Hotel de Mar in Sesimbra, Portugal, 15-17 February 1988. All the papers were edited afterwards. The Workshop encompassed several fields of Artificial Intelligence: Machine Learning, Belief Revision, Meta-Reasoning and Logics. The objective of this Workshop was not only to address the common issues in these areas, but also to examine how to elaborate cognitive architectures for systems capable of learning from experience, revising their beliefs and reasoning about what they know. Acknowledgements The editing of this book has been supported by COST-13 Project Machine Learning and Knowledge Acquisition funded by the Commission o/the European Communities which has covered a substantial part of the costs. Other sponsors who have supported this work were Junta Nacional de lnvestiga~ao Cientlfica (JNICT), lnstituto Nacional de lnvestiga~ao Cientlfica (INIC), Funda~ao Calouste Gulbenkian. I wish to express my gratitude to all these institutions. Finally my special thanks to Paula Pereira and AnaN ogueira for their help in preparing this volume. This work included retyping all the texts and preparing the camera-ready copy. Introduction 1 1. Meta-Reasoning and Machine Learning The first chapter is concerned with the role meta-reasoning plays in intelligent systems capable of learning. As we can see from the papers that appear in this chapter, there are basically two different schools of thought.


Metareasoning

Metareasoning

Author: Michael T. Cox

Publisher: MIT Press

Published: 2011

Total Pages: 349

ISBN-13: 0262014807

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Experts report on the latest artificial intelligence research concerning reasoning about reasoning itself.


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.


Inductive Logic Programming

Inductive Logic Programming

Author: Stephen Muggleton

Publisher: Morgan Kaufmann

Published: 1992

Total Pages: 602

ISBN-13: 9780125097154

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Inductive logic programming is a new research area emerging at present. Whilst inheriting various positive characteristics of the parent subjects of logic programming an machine learning, it is hoped that the new area will overcome many of the limitations of its forbears. This book describes the theory, implementations and applications of Inductive Logic Programming.


Book Synopsis Inductive Logic Programming by : Stephen Muggleton

Download or read book Inductive Logic Programming written by Stephen Muggleton and published by Morgan Kaufmann. This book was released on 1992 with total page 602 pages. Available in PDF, EPUB and Kindle. Book excerpt: Inductive logic programming is a new research area emerging at present. Whilst inheriting various positive characteristics of the parent subjects of logic programming an machine learning, it is hoped that the new area will overcome many of the limitations of its forbears. This book describes the theory, implementations and applications of Inductive Logic Programming.


Machine Learning Proceedings 1989

Machine Learning Proceedings 1989

Author: Machine Learning

Publisher: Morgan Kaufmann

Published: 2016-04-20

Total Pages: 510

ISBN-13: 1483297403

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Machine Learning Proceedings 1989


Book Synopsis Machine Learning Proceedings 1989 by : Machine Learning

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


Neural-Symbolic Cognitive Reasoning

Neural-Symbolic Cognitive Reasoning

Author: Artur S. D'Avila Garcez

Publisher: Springer Science & Business Media

Published: 2009

Total Pages: 200

ISBN-13: 3540732454

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This book explores why, regarding practical reasoning, humans are sometimes still faster than artificial intelligence systems. It is the first to offer a self-contained presentation of neural network models for many computer science logics.


Book Synopsis Neural-Symbolic Cognitive Reasoning by : Artur S. D'Avila Garcez

Download or read book Neural-Symbolic Cognitive Reasoning written by Artur S. D'Avila Garcez and published by Springer Science & Business Media. This book was released on 2009 with total page 200 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explores why, regarding practical reasoning, humans are sometimes still faster than artificial intelligence systems. It is the first to offer a self-contained presentation of neural network models for many computer science logics.


An Introduction to Fuzzy Logic Applications in Intelligent Systems

An Introduction to Fuzzy Logic Applications in Intelligent Systems

Author: Ronald R. Yager

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 358

ISBN-13: 1461536405

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An Introduction to Fuzzy Logic Applications in Intelligent Systems consists of a collection of chapters written by leading experts in the field of fuzzy sets. Each chapter addresses an area where fuzzy sets have been applied to situations broadly related to intelligent systems. The volume provides an introduction to and an overview of recent applications of fuzzy sets to various areas of intelligent systems. Its purpose is to provide information and easy access for people new to the field. The book also serves as an excellent reference for researchers in the field and those working in the specifics of systems development. People in computer science, especially those in artificial intelligence, knowledge-based systems, and intelligent systems will find this to be a valuable sourcebook. Engineers, particularly control engineers, will also have a strong interest in this book. Finally, the book will be of interest to researchers working in decision support systems, operations research, decision theory, management science and applied mathematics. An Introduction to Fuzzy Logic Applications in Intelligent Systems may also be used as an introductory text and, as such, it is tutorial in nature.


Book Synopsis An Introduction to Fuzzy Logic Applications in Intelligent Systems by : Ronald R. Yager

Download or read book An Introduction to Fuzzy Logic Applications in Intelligent Systems written by Ronald R. Yager and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 358 pages. Available in PDF, EPUB and Kindle. Book excerpt: An Introduction to Fuzzy Logic Applications in Intelligent Systems consists of a collection of chapters written by leading experts in the field of fuzzy sets. Each chapter addresses an area where fuzzy sets have been applied to situations broadly related to intelligent systems. The volume provides an introduction to and an overview of recent applications of fuzzy sets to various areas of intelligent systems. Its purpose is to provide information and easy access for people new to the field. The book also serves as an excellent reference for researchers in the field and those working in the specifics of systems development. People in computer science, especially those in artificial intelligence, knowledge-based systems, and intelligent systems will find this to be a valuable sourcebook. Engineers, particularly control engineers, will also have a strong interest in this book. Finally, the book will be of interest to researchers working in decision support systems, operations research, decision theory, management science and applied mathematics. An Introduction to Fuzzy Logic Applications in Intelligent Systems may also be used as an introductory text and, as such, it is tutorial in nature.


Machine Learning

Machine Learning

Author: Yves Kodratoff

Publisher: Elsevier

Published: 2014-06-28

Total Pages: 836

ISBN-13: 0080510558

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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.


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.


Machine Intelligence 15

Machine Intelligence 15

Author: Koichi Furukawa

Publisher: Oxford University Press

Published: 1999

Total Pages: 518

ISBN-13: 9780198538677

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The Machine Intelligence series was founded in 1965 by Donald Michie and has included many of the most important developments in the field over the past decades. This volume focuses on the theme of intelligent agents and features work by a number of eminent figures in artificial intelligence, including John McCarthy, Alan Robinson, Robert Kowalski, and Mike Genesereth. Topics include representations of consciousness, SoftBots, parallel implementations of logic, machine learning, machine vision, and machine-based scientific discovery in molecular biology.


Book Synopsis Machine Intelligence 15 by : Koichi Furukawa

Download or read book Machine Intelligence 15 written by Koichi Furukawa and published by Oxford University Press. This book was released on 1999 with total page 518 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Machine Intelligence series was founded in 1965 by Donald Michie and has included many of the most important developments in the field over the past decades. This volume focuses on the theme of intelligent agents and features work by a number of eminent figures in artificial intelligence, including John McCarthy, Alan Robinson, Robert Kowalski, and Mike Genesereth. Topics include representations of consciousness, SoftBots, parallel implementations of logic, machine learning, machine vision, and machine-based scientific discovery in molecular biology.


Machine Learning - EWSL-91

Machine Learning - EWSL-91

Author: Yves Kodratoff

Publisher: Springer Science & Business Media

Published: 1991-02-20

Total Pages: 554

ISBN-13: 9783540538165

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In this book contemporary knowledge of superconductivity is set against its historical background. First, the highlights of superconductivity research in the twentieth century are reviewed. Further contributions then describe the basic phenomena resulting from the macroscopic quantum state of superconductivity (such as zero resistivity, the Meissner-Ochsenfeld effect, and flux quantization) and review possible mechaniscs, including the classical BCS theory and the more recent alternative theories. The main categories of superconductors - elements, intermetallic phases, chalcogenides, oxides and organic compounds - are described. Common features and differences in their structure and electronic properties are pointed out. This broad overview of superconductivity is completed by a discussion of properties related to the coherence length. Newcomers to the field who seek an overall picture of research in superconductivity, and of the cross-links between its branches, will find this volume especially useful.


Book Synopsis Machine Learning - EWSL-91 by : Yves Kodratoff

Download or read book Machine Learning - EWSL-91 written by Yves Kodratoff and published by Springer Science & Business Media. This book was released on 1991-02-20 with total page 554 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this book contemporary knowledge of superconductivity is set against its historical background. First, the highlights of superconductivity research in the twentieth century are reviewed. Further contributions then describe the basic phenomena resulting from the macroscopic quantum state of superconductivity (such as zero resistivity, the Meissner-Ochsenfeld effect, and flux quantization) and review possible mechaniscs, including the classical BCS theory and the more recent alternative theories. The main categories of superconductors - elements, intermetallic phases, chalcogenides, oxides and organic compounds - are described. Common features and differences in their structure and electronic properties are pointed out. This broad overview of superconductivity is completed by a discussion of properties related to the coherence length. Newcomers to the field who seek an overall picture of research in superconductivity, and of the cross-links between its branches, will find this volume especially useful.


Machine Learning Proceedings 1991

Machine Learning Proceedings 1991

Author: Machine Learning

Publisher: Morgan Kaufmann

Published: 2014-06-28

Total Pages: 661

ISBN-13: 1483298175

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Machine Learning


Book Synopsis Machine Learning Proceedings 1991 by : Machine Learning

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