Machine Learning, Meta-Reasoning and Logics

Machine Learning, Meta-Reasoning and Logics PDF Author: Pavel B. Brazdil
Publisher: Springer Science & Business Media
ISBN: 1461316413
Category : Computers
Languages : en
Pages : 339

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Book Description
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.

Machine Learning, Meta-Reasoning and Logics

Machine Learning, Meta-Reasoning and Logics PDF Author: Pavel B. Brazdil
Publisher: Springer Science & Business Media
ISBN: 1461316413
Category : Computers
Languages : en
Pages : 339

Get Book

Book Description
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 PDF Author: Michael T. Cox
Publisher: MIT Press
ISBN: 0262014807
Category : Computers
Languages : en
Pages : 349

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

Inductive Logic Programming

Inductive Logic Programming PDF Author: Stephen Muggleton
Publisher: Morgan Kaufmann
ISBN: 9780125097154
Category : Computers
Languages : en
Pages : 602

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Book Description
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 PDF Author: Machine Learning
Publisher: Morgan Kaufmann
ISBN: 1483297403
Category : Computers
Languages : en
Pages : 510

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Book Description
Machine Learning Proceedings 1989

Neural-Symbolic Cognitive Reasoning

Neural-Symbolic Cognitive Reasoning PDF Author: Artur S. D'Avila Garcez
Publisher: Springer Science & Business Media
ISBN: 3540732454
Category : Computers
Languages : en
Pages : 200

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Book Description
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 PDF Author: Ronald R. Yager
Publisher: Springer Science & Business Media
ISBN: 1461536405
Category : Computers
Languages : en
Pages : 358

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Book Description
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.

Logics in Artificial Intelligence

Logics in Artificial Intelligence PDF Author: Steffen Hölldobler
Publisher: Springer Science & Business Media
ISBN: 3540878025
Category : Computers
Languages : en
Pages : 439

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Book Description
This book constitutes the refereed proceedings of the 11th European Conference on Logics in Artificial Intelligence, JELIA 2008, held in Dresden, Germany, Liverpool, in September/October 2008. The 32 revised full papers presented together with 2 invited talks were carefully reviewed and selected from 98 submissions. The papers cover a broad range of topics including belief revision, description logics, non-monotonic reasoning, multi-agent systems, probabilistic logic, and temporal logic.

Machine Learning

Machine Learning PDF Author: Yves Kodratoff
Publisher: Elsevier
ISBN: 0080510558
Category : Computers
Languages : en
Pages : 836

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Book Description
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 PDF Author: Koichi Furukawa
Publisher: Oxford University Press
ISBN: 9780198538677
Category : Business & Economics
Languages : en
Pages : 518

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Book Description
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 PDF Author: Yves Kodratoff
Publisher: Springer Science & Business Media
ISBN: 9783540538165
Category : Computers
Languages : en
Pages : 554

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Book Description
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.