Abstraction in Artificial Intelligence and Complex Systems
Jean-Daniel Zucker
Language: English
Pages: 484
ISBN: 146147051X
Format: PDF / Kindle (mobi) / ePub
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.
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Objects, but simply “diverts the attention from their peculiarities”. On the other hand, Frege himself appeared to change his position ten years later, by asserting that the process of abstraction can indeed change the objects, or even create new ones. In the Word iQ dictionary9 abstraction is defined as “the process of extracting the underlying essence of a mathematical concept, removing any dependence on real world objects with which it might originally have been connected, and generalizing it.
Lines, and so on. The art language of Western cultures had, in the past, a strict link with the reality that was to be communicated: arts were figurative. Later on, the language acquired more and more autonomy, and (at least parts of) the arts became abstract [219]. 10 “This is not a pipe”. 2.5 Art (Mostly Peinture) 29 Fig. 2.3 Nocturne in Black and Gold by J. McNeill Whistler (1875). It is considered as a first step toward abstraction in painting [A color version of this figure is reported.
Intermediate representation based on G¨ardenfors’ notion of conceptual space [194]. This intermediate level is where abstractions, intended as meaningful groupings of pixels from the external world, are formed. In addition, a mechanism of focus of attention, allowing only relevant aspects of the input signal to be kept, implements another type of abstraction. As we mentioned at the beginning of this section, abstraction is the primary mechanism that allows us to make sense of the visual world we.
Nothing more than the set of its properties. Things become even more complex when the term object starts to denote also immaterial or conceptual things. As mentioned in Sect. 2.4, in Computer Science the notion of object is associated to that of abstract data types, and is the basis for object-oriented programming. This association is particularly relevant for developing models of abstraction, specifically via the idea of encapsulation, which is exactly the information hiding or aggregating.
Observables of a LoA are defined, it is usually the case that not all the combinations of possible values for the observables are realizable. The behavior aims at capturing only those combinations that are actually possible. LoAs are then linked to the notion of granularity in describing systems, and Floridi takes a further step by allowing multiple LoAs. To this aim, the notion of relation must be recalled. Definition 4.14 (Relation) Given a set A and a set C, a relation R from A to C is a.