Readings in Artificial Intelligence and Databases

Readings in Artificial Intelligence and Databases PDF Author: John Mylopoulos
Publisher: Morgan Kaufmann
ISBN: 0080886620
Category : Computers
Languages : en
Pages : 697

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Book Description
The interaction of database and AI technologies is crucial to such applications as data mining, active databases, and knowledge-based expert systems. This volume collects the primary readings on the interactions, actual and potential, between these two fields. The editors have chosen articles to balance significant early research and the best and most comprehensive articles from the 1980s. An in-depth introduction discusses basic research motivations, giving a survey of the history, concepts, and terminology of the interaction. Major themes, approaches and results, open issues and future directions are all discussed, including the results of a major survey conducted by the editors of current work in industry and research labs. Thirteen sections follow, each with a short introduction. Topics examined include semantic data models with emphasis on conceptual modeling techniques for databases and information systems and the integration of data model concepts in high-level data languages, definition and maintenance of integrity constraints in databases and knowledge bases, natural language front ends, object-oriented database management systems, implementation issues such as concurrency control and error recovery, and representation of time and knowledge incompleteness from the viewpoints of databases, logic programming, and AI.

Readings in Artificial Intelligence and Databases

Readings in Artificial Intelligence and Databases PDF Author: John Mylopoulos
Publisher: Morgan Kaufmann
ISBN: 0080886620
Category : Computers
Languages : en
Pages : 697

Get Book Here

Book Description
The interaction of database and AI technologies is crucial to such applications as data mining, active databases, and knowledge-based expert systems. This volume collects the primary readings on the interactions, actual and potential, between these two fields. The editors have chosen articles to balance significant early research and the best and most comprehensive articles from the 1980s. An in-depth introduction discusses basic research motivations, giving a survey of the history, concepts, and terminology of the interaction. Major themes, approaches and results, open issues and future directions are all discussed, including the results of a major survey conducted by the editors of current work in industry and research labs. Thirteen sections follow, each with a short introduction. Topics examined include semantic data models with emphasis on conceptual modeling techniques for databases and information systems and the integration of data model concepts in high-level data languages, definition and maintenance of integrity constraints in databases and knowledge bases, natural language front ends, object-oriented database management systems, implementation issues such as concurrency control and error recovery, and representation of time and knowledge incompleteness from the viewpoints of databases, logic programming, and AI.

AI Magazine

AI Magazine PDF Author:
Publisher:
ISBN:
Category : Artificial intelligence
Languages : en
Pages : 600

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Book Description


Readings in Distributed Artificial Intelligence

Readings in Distributed Artificial Intelligence PDF Author: Alan H. Bond
Publisher: Morgan Kaufmann
ISBN: 1483214443
Category : Computers
Languages : en
Pages : 668

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Book Description
Most artificial intelligence research investigates intelligent behavior for a single agent--solving problems heuristically, understanding natural language, and so on. Distributed Artificial Intelligence (DAI) is concerned with coordinated intelligent behavior: intelligent agents coordinating their knowledge, skills, and plans to act or solve problems, working toward a single goal, or toward separate, individual goals that interact. DAI provides intellectual insights about organization, interaction, and problem solving among intelligent agents. This comprehensive collection of articles shows the breadth and depth of DAI research. The selected information is relevant to emerging DAI technologies as well as to practical problems in artificial intelligence, distributed computing systems, and human-computer interaction. "Readings in Distributed Artificial Intelligence" proposes a framework for understanding the problems and possibilities of DAI. It divides the study into three realms: the natural systems approach (emulating strategies and representations people use to coordinate their activities), the engineering/science perspective (building automated, coordinated problem solvers for specific applications), and a third, hybrid approach that is useful in analyzing and developing mixed collections of machines and human agents working together. The editors introduce the volume with an important survey of the motivations, research, and results of work in DAI. This historical and conceptual overview combines with chapter introductions to guide the reader through this fascinating field. A unique and extensive bibliography is also provided.

The AI Magazine

The AI Magazine PDF Author:
Publisher:
ISBN:
Category : Artificial intelligence
Languages : en
Pages : 128

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Book Description


An Introduction to Artificial Intelligence

An Introduction to Artificial Intelligence PDF Author: Kenneth H. Rose
Publisher:
ISBN:
Category : Artificial intelligence
Languages : en
Pages : 178

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Book Description


Readings in Machine Learning

Readings in Machine Learning PDF Author: Jude W. Shavlik
Publisher: Morgan Kaufmann
ISBN: 9781558601437
Category : Computers
Languages : en
Pages : 868

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Book Description
The ability to learn is a fundamental characteristic of intelligent behavior. Consequently, machine learning has been a focus of artificial intelligence since the beginnings of AI in the 1950s. The 1980s saw tremendous growth in the field, and this growth promises to continue with valuable contributions to science, engineering, and business. Readings in Machine Learning collects the best of the published machine learning literature, including papers that address a wide range of learning tasks, and that introduce a variety of techniques for giving machines the ability to learn. The editors, in cooperation with a group of expert referees, have chosen important papers that empirically study, theoretically analyze, or psychologically justify machine learning algorithms. The papers are grouped into a dozen categories, each of which is introduced by the editors.

Readings in Intelligent User Interfaces

Readings in Intelligent User Interfaces PDF Author: Mark Maybury
Publisher: Morgan Kaufmann
ISBN: 9781558604445
Category : Computers
Languages : en
Pages : 670

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Book Description
This is a compilation of the classic readings in intelligent user interfaces. This text focuses on intelligent, knowledge-based interfaces, combining spoken language, natural language processing, and multimedia and multimodal processing.

Essentials of Artificial Intelligence

Essentials of Artificial Intelligence PDF Author: Matt Ginsberg
Publisher: Newnes
ISBN: 032313968X
Category : Computers
Languages : en
Pages : 445

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Book Description
Since its publication, Essentials of Artificial Intelligence has been adopted at numerous universities and colleges offering introductory AI courses at the graduate and undergraduate levels. Based on the author's course at Stanford University, the book is an integrated, cohesive introduction to the field. The author has a fresh, entertaining writing style that combines clear presentations with humor and AI anecdotes. At the same time, as an active AI researcher, he presents the material authoritatively and with insight that reflects a contemporary, first hand understanding of the field. Pedagogically designed, this book offers a range of exercises and examples.

Machine Learning

Machine Learning PDF Author: Ryszard S. Michalski
Publisher: Morgan Kaufmann
ISBN: 9781558602519
Category : Computers
Languages : en
Pages : 798

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Book Description
Multistrategy learning is one of the newest and most promising research directions in the development of machine learning systems. The objectives of research in this area are to study trade-offs between different learning strategies and to develop learning systems that employ multiple types of inference or computational paradigms in a learning process. Multistrategy systems offer significant advantages over monostrategy systems. They are more flexible in the type of input they can learn from and the type of knowledge they can acquire. As a consequence, multistrategy systems have the potential to be applicable to a wide range of practical problems. This volume is the first book in this fast growing field. It contains a selection of contributions by leading researchers specializing in this area. See below for earlier volumes in the series.

Readings in Agents

Readings in Agents PDF Author: Michael N. Huhns
Publisher: Morgan Kaufmann
ISBN: 9781558604957
Category : Computers
Languages : en
Pages : 552

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Book Description
This book collects the most significant literature on agents in an attempt top forge a broad foundation for the field. Includes papers from the perspectives of AI, databases, distributed computing, and programming languages. The book will be of interest to programmers and developers, especially in Internet areas.