Lorenza Saitta, Jean-Daniel Zucker (auth.)'s Abstraction in artificial intelligence and complex systems PDF

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

ISBN-10: 146147051X

ISBN-13: 9781461470519

ISBN-10: 1461470528

ISBN-13: 9781461470526

Abstraction is a basic mechanism underlying either human and synthetic belief, illustration of information, reasoning and studying. This mechanism performs an important function in lots of disciplines, particularly computing device Programming, typical and synthetic imaginative and prescient, complicated platforms, man made Intelligence and desktop studying, artwork, and Cognitive Sciences. This publication first offers the reader with an summary of the notions of abstraction proposed in a number of disciplines via evaluating either commonalities and adjustments. After discussing the characterizing homes of abstraction, a proper version, the KRA version, is gifted to trap them. This version makes the idea of abstraction simply appropriate through the advent of a suite of abstraction operators and abstraction styles, reusable throughout diversified domain names and functions. it's the impression of abstraction in synthetic Intelligence, advanced platforms and computing device studying which creates the middle of the e-book. A common framework, in keeping with the KRA version, is gifted, and its pragmatic strength is illustrated with 3 case reviews: Model-based analysis, Cartographic Generalization, and studying Hierarchical Hidden Markov Models.

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These authors define other types of abstraction as well, which will be described in Sect. 2. Colburn and Shute [111] make a point is differentiating Computer Science from empirical sciences, because the latter ones have concrete models in the form of experimental apparata as well as abstract mathematical models, whereas the former has only software models, which are not physically concrete. , the use of formalism), and the objectives. The main reason of abstraction in Mathematics are inference structures (theorems and their proofs), while in Computer Science it is interaction patterns (pieces of software).

1 Suppose that we want to write a procedure for searching whether an element y appears in a vector X without specifying the actual program to do it. We can define the following abstract procedure: pname = Search(X, y) returns({true, false}) requires X is a vector, y is of the same type as the elements of X modifies ∅ effects Searches through X , and returns true if y occurs in X , else returns false end pname Data abstraction, on the other hand, consists in defining a type of data and the operations that manipulate it.

The relationship between classes, objects and data abstraction has been investigated by Fisher and Mitchell [170], who compare three approaches to class-based programming, namely, one called “premethods”, and two others called “prototype”. The authors claim that object-based methods are superior to class-based ones. Introducing an ADT leads spontaneously to the idea of several nested layers of abstraction [170]. A data type may be part of an is-a hierarchy, organized as a tree, where each node has one father, but may have several children.

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Abstraction in artificial intelligence and complex systems by Lorenza Saitta, Jean-Daniel Zucker (auth.)


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