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Abstraction in artificial intelligence and complex systems

Author: Lorenza Saitta; Jean-Daniel Zucker
Publisher: New York, NY : Springer, ©2013.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Database:WorldCat
Summary:
Abstraction is a fundamental mechanism underlying both human and artificial perception, representation of knowledge, reasoning and learning. This mechanism plays a crucial role in many disciplines, notably Computer Programming, Natural and Artificial Vision, Complex Systems, Artificial Intelligence and Machine Learning, Art, and Cognitive Sciences. This book first provides the reader with an overview of the notions  Read more...
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Genre/Form: Electronic books
Additional Physical Format: Original print version: Saitta, L. (Lorenza), 1944-
Abstraction in artificial intelligence and complex systems.
New York : Springer, [2013]
(DLC) 2013934382
(OCoLC)828487502
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Lorenza Saitta; Jean-Daniel Zucker
ISBN: 9781461470526 1461470528 146147051X 9781461470519
OCLC Number: 847976995
Description: 1 online resource (xvi, 484 pages) : ill. (some col.)
Contents: Introduction --
Abstraction in Different Disciplines --
Abstraction in Artificial Intelligence --
Definitions of Abstraction --
Boundaries of Abstraction --
The KRA KRA Model --
Abstraction Operators and Design Patterns --
Properties of the KRA Model --
Abstraction in Machine Learning --
Simplicity, Complex Systems, and Abstraction --
Case Studies and Applications --
Discussion --
Conclusion.
Responsibility: Lorenza Saitta, Jean-Daniel Zucker.

Abstract:

Abstraction is a fundamental mechanism underlying both human and artificial perception, representation of knowledge, reasoning and learning. This mechanism plays a crucial role in many disciplines, notably Computer Programming, Natural and Artificial Vision, Complex Systems, Artificial Intelligence and Machine Learning, Art, and Cognitive Sciences. This book first provides the reader with an overview of the notions of abstraction proposed in various disciplines by comparing both commonalities and differences. After discussing the characterizing properties of abstraction, a formal model, the KRA model, is presented to capture them. This model makes the notion of abstraction easily applicable by means of the introduction of a set of abstraction operators and abstraction patterns, reusable across different domains and applications. It is the impact of abstraction in Artificial Intelligence, Complex Systems and Machine Learning which creates the core of the book. A general framework, based on the KRA model, is presented, and its pragmatic power is illustrated with three case studies: Model-based diagnosis, Cartographic Generalization, and learning Hierarchical Hidden Markov Models.

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