03098nam 2200505Ia 450 991073698520332120200520144314.01-4614-7052-810.1007/978-1-4614-7052-6(OCoLC)847976995(MiFhGG)GVRL6VJE(CKB)2560000000103586(MiAaPQ)EBC1317297(EXLCZ)99256000000010358620130301d2013 uy 0engurun|---uuuuatxtccrAbstraction in artificial intelligence and complex systems /Lorenza Saitta, Jean-Daniel Zucker1st ed. 2013.New York Springer20131 online resource (xvi, 484 pages) illustrations (chiefly color)Gale eBooksDescription based upon print version of record.1-4899-8874-2 1-4614-7051-X Includes bibliographical references and index.Introduction -- Abstraction in Different Disciplines -- Abstraction in Artificial Intelligence -- Definitions of Abstraction -- Boundaries of Abstraction -- The KRA Model -- Abstraction Operators and Design Patterns -- Properties of the KRA Model -- Abstraction in Machine Learning -- Simplicity, Complex Systems, and Abstraction -- Case Studies and Applications -- Discussion -- Conclusion.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.Artificial intelligenceAbstractionArtificial intelligence.Abstraction.006.3Saitta L(Lorenza),1944-1750226Zucker Jean-Daniel1750227MiAaPQMiAaPQMiAaPQBOOK9910736985203321Abstraction in artificial intelligence and complex systems4184808UNINA