Abstraction in Artificial Intelligence and Complex Systems
Saitta, Lorenza, Zucker, Jean-Daniel
2013, XVI, 484 p. 202 illus., 95 illus. in color.
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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
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.