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

By Lorenza Saitta, Jean-Daniel Zucker

▓ Book's spouse Website

▓ 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, significantly computing device Programming, normal and synthetic imaginative and prescient, advanced structures, synthetic Intelligence and desktop studying, paintings, and Cognitive Sciences. This ebook first offers the reader with an outline of the notions of abstraction proposed in numerous disciplines through evaluating either commonalities and variations. After discussing the characterizing houses of abstraction, a proper version, the KRA version, is gifted to trap them. This version makes the idea of abstraction simply acceptable by way of the advent of a collection of abstraction operators and abstraction styles, reusable throughout diverse domain names and functions. it's the impression of abstraction in synthetic Intelligence, complicated structures and laptop studying which creates the middle of the booklet. A basic framework, in accordance with the KRA version, is gifted, and its pragmatic energy is illustrated with 3 case stories: Model-based prognosis, Cartographic Generalization, and studying Hierarchical Hidden Markov Models.
∙ Collects, describes and compares a number of methods to abstraction proposed within the literature of assorted fields
∙ Discusses why abstraction performs a key position in AI artifacts, utilizing concrete examples, comparable to cartographic generalization and human/robot interaction
∙ presents a conceptualization framework to layout potent systems

▒ Book's Preface
When we all started scripting this ebook we have been conscious of the complexity of the task,
but we didn't think that it should take us nearly 3 years to accomplish it.
Furthermore, through the research and comparability of the literature from different
fields, it essentially emerged that vital effects were accomplished, yet that much
more very important ones are nonetheless out of succeed in. Then, the spirit of the ebook replaced, by
itself, from the meant review of the prior to a stimulus for the longer term. We
would be at liberty if the reader, rather than being content material with the guidelines we propose,
would take them as a motivation and start line to head past them.
We current a wide number of works on abstraction in numerous disciplines;
nonetheless many suitable contributions to the sector were unavoidably left out,
owing to the sheer volume of pages they'd fill. We express regret for the missing
In this booklet we current a version of abstraction, the KRA version, yet this can be not
the center of the booklet. It has a restricted scope and serves major reasons: on the
one hand it indicates that numerous earlier 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 setting for appearing abstraction through utilising a collection of
available, domain-independent operators (programs). in reality, there's nonetheless a gap
between basic abstraction theories, often dependent logical formulations of representation
changes, and urban methods that seriously depend on particular domain
characteristics. The KRA version is intended to be whatever in among: the
domain-independence of the abstraction operators achieves either generality (it can
cover a extensive spectrum of functions 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 strictly what he/she has always
looked for, while another may perhaps imagine that abstraction is completely something
else. either reactions are welcome: what concerns is to set off curiosity within the subject
and stimulate extra research.
The publication isn't meant to be a textbook: it's certain to scientists operating on
or utilizing abstraction innovations, with no trouble of fields. desktop scientists,
Artificial Intelligence researchers, artists, cognitive scientists, mathematicians, and curious minds can learn the e-book. a few elements are extra formalized, and so they may
look advanced at the start sight. although, we think that the best a part of the
content is graspable via intuition.

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Extra info for Abstraction in Artificial Intelligence and Complex Systems

Sample text

It is thus important to establish relations among them. To this end, Floridi introduces n} the concept of Gradient of Abstraction (GoA), which is a finite set {L i |1 i of moderated LoAs, and a set of relations relating the observables belonging to pairs of LoAs. A GoA can be disjoint or nested. Informally, a disjoint GoA is a collection of unrelated LoAs, whereas a nested one contains a set of LoAs that are refinements one of another. 6 An observable does not necessarily correspond to a physically measurable entity, because the system under analysis may be a conceptual one.

The essence was reached by throwing away peculiarities of instances, and keeping universal and essential aspects. This idea of abstraction did not necessarily imply, at the beginning, moving away from the figurative. But, once accepted that the goal of art was to attain the essence and not to faithfully represent reality, the door to non-figurative art was open. An example of this process is reported in Fig. 6, due to Theo van Doesbourg, an early abstraction painter, who, together with Piet Mondrian, founded the journal De Stijl.

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.

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