Abstraction in Artificial Intelligence and Complex Systems by Lorenza Saitta, Jean-Daniel Zucker

By Lorenza Saitta, Jean-Daniel Zucker

▓ Book's better half Website

▓ Abstraction is a primary mechanism underlying either human and synthetic belief, illustration of data, reasoning and studying. This mechanism performs a very important function in lots of disciplines, particularly desktop Programming, ordinary and synthetic imaginative and prescient, advanced platforms, man made Intelligence and computer studying, paintings, and Cognitive Sciences. This booklet first presents the reader with an outline of the notions of abstraction proposed in quite a few disciplines through 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 proposal of abstraction simply appropriate via the advent of a collection of abstraction operators and abstraction styles, reusable throughout assorted domain names and purposes. it's the impression of abstraction in synthetic Intelligence, advanced platforms and computer studying which creates the center of the booklet. A common framework, in keeping with the KRA version, is gifted, and its pragmatic strength is illustrated with 3 case reports: Model-based prognosis, Cartographic Generalization, and studying Hierarchical Hidden Markov Models.
∙ Collects, describes and compares a number of techniques to abstraction proposed within the literature of assorted fields
∙ Discusses why abstraction performs a key position in AI artifacts, utilizing concrete examples, corresponding to cartographic generalization and human/robot interaction
∙ offers a conceptualization framework to layout powerful systems

▒ Book's Preface
When we all started penning this publication we have been conscious of the complexity of the task,
but we didn't think that it is going to take us nearly 3 years to accomplish it.
Furthermore, throughout the research and comparability of the literature from different
fields, it basically emerged that very important effects were accomplished, yet that much
more very important ones are nonetheless out of succeed in. Then, the spirit of the e-book replaced, by
itself, from the meant overview of the prior to a stimulus for the longer term. We
would feel free if the reader, rather than being content material with the information we propose,
would take them as a motivation and place to begin to move past them.
We current a wide choice of works on abstraction in different disciplines;
nonetheless many correct contributions to the sector were unavoidably left out,
owing to the sheer quantity of pages they'd fill. We make an apology for the missing
In this booklet we current a version of abstraction, the KRA version, yet this is often not
the middle of the publication. It has a restricted scope and serves major reasons: on the
one hand it indicates that a number of past proposals of abstraction theories have a
common root and will be dealt with inside of a unified framework, and, at the different, it
offers a computational surroundings for appearing abstraction via employing a suite of
available, domain-independent operators (programs). in reality, there's nonetheless a gap
between basic abstraction theories, normally dependent logical formulations of representation
changes, and urban techniques that seriously depend on particular domain
characteristics. The KRA version is intended to be anything in among: the
domain-independence of the abstraction operators achieves either generality (it can
cover a large spectrum of purposes and alertness domains), and synergy (by
instantiating in several contexts a few code written only one time).
Independently of the version, we think that the elemental principles on which it relies
are extra very important than the version itself. those principles are definitely controversial; some
reader may imagine that our view of abstraction is precisely what he/she has always
looked for, while another could imagine that abstraction is completely something
else. either reactions are welcome: what issues is to set off curiosity within the subject
and stimulate extra research.
The e-book isn't meant to be a textbook: it's designated to scientists operating on
or utilizing abstraction thoughts, with no difficulty of fields. desktop scientists,
Artificial Intelligence researchers, artists, cognitive scientists, mathematicians, and curious minds can learn the publication. a few components are extra formalized, and so they may
look advanced at the start sight. in spite of the fact that, we think that the best a part of the
content is graspable via intuition.

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In order to select the appropriate level, database designers exploit hierarchies over the values of variables. For instance, for a time variable, hour, day, week, month, and year constitute a hierarchy of values of increasing coarseness. In an analogous way, city, region, country constitute a hierarchy for a location variable. In relational algebra, several among the operators can be interpreted, in an intuitive sense, as abstraction operators. For instance, given a relational table R with attributes (A1 , .

An approach similar in spirit to Marr’s has been described by Pylyshyn [436], who suggested a semantic, syntactic, and physical level of systems description; an additional level of functional architecture acts as a bridge between Marr’s algorithmic and implementation levels. 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.

However this does not seem to be true for monkeys. A hypothesis about the nature of the processing was investigated very recently by Girard and Koening-Robert [211]. They argue that fast categorization could rely on the quantity of relevant information contained in the low spatial frequencies, because these last could allow a quick hypothesis about the content of the image to be built up. It would be very interesting to come up with a theory of abstraction capable of explaining (or, at least, describing) such a challenging phenomenon.

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