By Lorenza Saitta, Jean-Daniel Zucker (auth.)

Abstraction is a basic mechanism underlying either human and synthetic belief, illustration of data, reasoning and studying. This mechanism performs a vital position in lots of disciplines, particularly laptop Programming, traditional and synthetic imaginative and prescient, advanced structures, synthetic Intelligence and computing device studying, paintings, and Cognitive Sciences. This ebook first presents the reader with an summary of the notions of abstraction proposed in a variety of disciplines via evaluating either commonalities and transformations. After discussing the characterizing houses of abstraction, a proper version, the KRA version, is gifted to catch them. This version makes the suggestion of abstraction simply appropriate by way of the advent of a suite of abstraction operators and abstraction styles, reusable throughout diversified domain names and purposes. it's the effect of abstraction in man made Intelligence, advanced platforms and computing device studying which creates the middle of the ebook. A common framework, in accordance with the KRA version, is gifted, and its pragmatic energy is illustrated with 3 case reports: Model-based analysis, Cartographic Generalization, and studying Hierarchical Hidden Markov Models.

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Different levels of abstraction for the same system are appropriate for different goals. Each level “sees” the system under a specific perspective. The definition of a level of abstraction is only the first step in the analysis of a system. In fact, taken in isolation, each observable might take on values that are incompatible with those assumed by some others. Then, Floridi introduces a predicate over the observables, which is true only if the values assumed by the observables correspond to a feasible behavior of the system.

The connectionist view of abstraction suffers from the problem of concept complexity, as neural nets have difficulties in representing structured scenarios. 6 Cognition 33 Abstraction as a representation of a category is contrasted by Barsalou with the exemplar representation. In this context, abstraction is intended as a synthesis of common properties associated to a category, as opposed to the memorization of a set of concrete exemplars of the category itself. The two representations are compared in terms of information storage, revision, and loss, and in terms of types of processing that they support.

Finally, a third hierarchy, referring to levels of explanation, has been proposed by Dennet [133], who distinguishes three stances: the intentional stance, which sees the system under analysis as a rational agent performing a task; the design stance, concerning the principles that guide the design of a system successfully performing that task; and the physical stance, which considers the physical construction of a system according to these principles. In a recent paper, Weslake makes an interesting connection between explanatory depth and abstraction [559].

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