Abstraction in Artificial Intelligence and Complex Systems
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Author
Contributions
- Zucker, Jean-Daniel - Contributor
- SpringerLink (Online service) - Contributor
Publication
2013 - Imprint: Springer, New York, NY, United States
Language
English
Word Count
121,000 words, Guess
Page Count
484 pages
Physical Format
Electronic resource
Identifiers
- Open LibraryOL27014205M
- ISBN-139781461470526
Classifications
- DDC006.3
- LCCQ334-342
- LCCTJ210.2-211.495
and 1 more
- LCCQA75.5-76.95
Description
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.
Subjects
Other Editions
- Abstraction in Artificial Intelligence and Complex Systems
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