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Abstraction in Artificial Intelligence and Complex Systems

  • Book
  • © 2013

Overview

Authors:
  1. Lorenza Saitta

    1. , Dipartimento di Scienze e Innovazione Te, Università Degli Studi Del Piemonte Orie, Alessandria, Italy

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  2. Jean-Daniel Zucker

    1. , International Research Unit UMMISCO 209, Research Institute for Development (IRD), Bondy, France

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    You can also search for this author in PubMed   Google Scholar

  • Collects, describes and compares various approaches to abstraction proposed in the literature of various fields
  • Discusses why abstraction plays a key role in AI artifacts, using concrete examples, such as cartographic generalization and human/robot interaction
  • Provides a conceptualization framework to design effective systems
  • Includes supplementary material: sn.pub/extras

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Table of contents (13 chapters)

  1. Front Matter

    Pages i-xvi
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  2. Introduction

    • Lorenza Saitta, Jean-Daniel Zucker
    Pages 1-9

  3. Abstraction in Different Disciplines

    • Lorenza Saitta, Jean-Daniel Zucker
    Pages 11-47

  4. Abstraction in Artificial Intelligence

    • Lorenza Saitta, Jean-Daniel Zucker
    Pages 49-63

  5. Definitions of Abstraction

    • Lorenza Saitta, Jean-Daniel Zucker
    Pages 65-116

  6. Boundaries of Abstraction

    • Lorenza Saitta, Jean-Daniel Zucker
    Pages 117-139

  7. The \(\mathcal{KRA }\) Model

    • Lorenza Saitta, Jean-Daniel Zucker
    Pages 141-177

  8. Abstraction Operators and Design Patterns

    • Lorenza Saitta, Jean-Daniel Zucker
    Pages 179-222

  9. Properties of the \(\mathcal{KRA }\) Model

    • Lorenza Saitta, Jean-Daniel Zucker
    Pages 223-271

  10. Abstraction in Machine Learning

    • Lorenza Saitta, Jean-Daniel Zucker
    Pages 273-327

  11. Simplicity, Complex Systems, and Abstraction

    • Lorenza Saitta, Jean-Daniel Zucker
    Pages 329-362

  12. Case Studies and Applications

    • Lorenza Saitta, Jean-Daniel Zucker
    Pages 363-387

  13. Discussion

    • Lorenza Saitta, Jean-Daniel Zucker
    Pages 389-405

  14. Conclusion

    • Lorenza Saitta, Jean-Daniel Zucker
    Pages 407-411

  15. Back Matter

    Pages 413-484
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Keywords

About this book

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.

Authors and Affiliations

  • , Dipartimento di Scienze e Innovazione Te, Università Degli Studi Del Piemonte Orie, Alessandria, Italy

    Lorenza Saitta

  • , International Research Unit UMMISCO 209, Research Institute for Development (IRD), Bondy, France

    Jean-Daniel Zucker

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