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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.

Abstraction. --- Artificial intelligence -- Philosophy. --- Computer science. --- Artificial intelligence --- Abstraction --- Mechanical Engineering --- Engineering & Applied Sciences --- Computer Science --- Mechanical Engineering - General --- Philosophy --- Information Technology --- Artificial Intelligence --- Artificial intelligence. --- Abstract thought --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Data mining. --- Image processing. --- Application software. --- Computer Science. --- Artificial Intelligence (incl. Robotics). --- Image Processing and Computer Vision. --- Data Mining and Knowledge Discovery. --- Computer Appl. in Arts and Humanities. --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Cognition --- Logic --- Thought and thinking --- Computer vision. --- Information systems. --- Artificial Intelligence. --- Machine vision --- Vision, Computer --- Image processing --- Pattern recognition systems --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Database searching --- Optical data processing. --- Application computer programs --- Application computer software --- Applications software --- Apps (Computer software) --- Computer software --- Optical computing --- Visual data processing --- Integrated optics --- Photonics --- Computers --- Optical equipment --- Philosophy.

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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.

Human sciences (algemeen) --- Computer science --- Information systems --- Artificial intelligence. Robotics. Simulation. Graphics --- Computer. Automation --- computervisie --- beeldverwerking --- machine learning --- computers --- informatica --- sociale wetenschappen --- informatiesystemen --- database management --- KI (kunstmatige intelligentie) --- computerkunde --- robots --- data acquisition --- AI (artificiële intelligentie) --- Artificial intelligence. --- Abstraction.

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Artificial intelligence --- Intel·ligència artificial --- Mineria de dades --- Intel·ligència artificial.

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Cet ouvrage s'adresse aux étudiants de master des universités et aux élèves des écoles d'ingénieurs ainsi qu'aux mathématiciens, informaticiens et chercheurs de diverses disciplines qui sont amenés à créer des modèles dans leur domaine. La modélisation informatique à base d'agents permet de modéliser, à l'échelle macroscopique, des systèmes complexes à partir du comportement à l'échelle microscopique d'un grand nombre de leurs composants. L'objectif de ce livre se décline en cinq points complémentaires : Présenter au lecteur un panorama des approches de modélisation et simulation à base d'agents sous la forme de 11 exemples représentatifs puisés dans différents domaines scientifiques et technologiques. Proposer un cadre commun de définitions et une ébauche de démarche de conception qui permettent de fournir, au-delà de leur diversité apparente, une base sinon théorique du moins pratique de ces approches. Présenter les outils informatiques existants pour concevoir, spécifier, programmer et exploiter ces modèles. Introduire des approches mathématiques pour spécifier les comportements individuels des agents, caractériser leur comportement global, et effectuer les changements d'échelle concernés. Aborder, enfin, les questions de recherche soulevées par l'usage de ces approches dans le cadre de la modélisation des systèmes complexes. Chaque chapitre a été conçu pour répondre aux questions que peuvent se poser les lecteurs qui découvrent ce nouveau paradigme ou à ceux qui le connaissent mais souhaitent aller plus loin.--Résumé de l'éditeur

Simulation methods --- Management science --- Digital computer simulation