Isbn: 9786209827075 - computational framework for adaptive artificial intelligence (9 risultati)

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  • Lingua: Inglese

    Editore: LAP Lambert Academic Publishing, 2026

    6209827071 / 9786209827075

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  • Lingua: Inglese

    Editore: LAP LAMBERT Academic Publishing, 2026

    6209827071 / 9786209827075

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  • Lingua: Inglese

    Editore: LAP LAMBERT Academic Publishing, 2026

    6209827071 / 9786209827075

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  • Lingua: Inglese

    Editore: LAP LAMBERT Academic Publishing, 2026

    6209827071 / 9786209827075

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    Taschenbuch. Condizione: Neu. COMPUTATIONAL FRAMEWORK FOR ADAPTIVE ARTIFICIAL INTELLIGENCE | Jayashree Ananth S | Taschenbuch | Englisch | 2026 | LAP LAMBERT Academic Publishing | EAN 9786209827075 | Verantwortliche Person für die EU: SIA OmniScriptum Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu.

  • Lingua: Inglese

    Editore: LAP Lambert Academic Publishing, 2026

    6209827071 / 9786209827075

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    Paperback. Condizione: new. Paperback. The development of a computational framework for adaptive artificial intelligence represents a transformative shift in the evolution of intelligent systems. Throughout this book, we have examined the theoretical foundations, algorithmic principles, architectural designs, and ethical implications that collectively define adaptive AI. At its core, adaptive artificial intelligence refers to systems that possess the capacity to learn continuously from data, modify internal representations in response to environmental changes, and improve performance without explicit reprogramming. Unlike traditional static models that rely on predefined rules or fixed training phases, adaptive AI systems operate in dynamic environments where uncertainty, variability, and incomplete information are inherent characteristics. The integration of computational intelligence methods, machine learning paradigms, reinforcement learning strategies, neural network architectures, and systems engineering principles forms the backbone of this adaptive framework. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

  • Lingua: Inglese

    Editore: LAP LAMBERT Academic Publishing Mär 2026, 2026

    6209827071 / 9786209827075

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    Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.

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    Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 144 pp. Englisch.

  • Lingua: Inglese

    Editore: LAP Lambert Academic Publishing, 2026

    6209827071 / 9786209827075

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    Da: CitiRetail, Stevenage, Regno UnitoCitiRetail

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    Paperback. Condizione: new. Paperback. The development of a computational framework for adaptive artificial intelligence represents a transformative shift in the evolution of intelligent systems. Throughout this book, we have examined the theoretical foundations, algorithmic principles, architectural designs, and ethical implications that collectively define adaptive AI. At its core, adaptive artificial intelligence refers to systems that possess the capacity to learn continuously from data, modify internal representations in response to environmental changes, and improve performance without explicit reprogramming. Unlike traditional static models that rely on predefined rules or fixed training phases, adaptive AI systems operate in dynamic environments where uncertainty, variability, and incomplete information are inherent characteristics. The integration of computational intelligence methods, machine learning paradigms, reinforcement learning strategies, neural network architectures, and systems engineering principles forms the backbone of this adaptive framework. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

  • Lingua: Inglese

    Editore: LAP LAMBERT Academic Publishing Mär 2026, 2026

    6209827071 / 9786209827075

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    Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000

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    Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The development of a computational framework for adaptive artificial intelligence represents a transformative shift in the evolution of intelligent systems. Throughout this book, we have examined the theoretical foundations, algorithmic principles, architectural designs, and ethical implications that collectively define adaptive AI. At its core, adaptive artificial intelligence refers to systems that possess the capacity to learn continuously from data, modify internal representations in response to environmental changes, and improve performance without explicit reprogramming. Unlike traditional static models that rely on predefined rules or fixed training phases, adaptive AI systems operate in dynamic environments where uncertainty, variability, and incomplete information are inherent characteristics. The integration of computational intelligence methods, machine learning paradigms, reinforcement learning strategies, neural network architectures, and systems engineering principles forms the backbone of this adaptive framework.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 144 pp. Englisch.

  • Lingua: Inglese

    Editore: LAP LAMBERT Academic Publishing, 2026

    6209827071 / 9786209827075

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    Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH

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    EUR 159,65

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    Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The development of a computational framework for adaptive artificial intelligence represents a transformative shift in the evolution of intelligent systems. Throughout this book, we have examined the theoretical foundations, algorithmic principles, architectural designs, and ethical implications that collectively define adaptive AI. At its core, adaptive artificial intelligence refers to systems that possess the capacity to learn continuously from data, modify internal representations in response to environmental changes, and improve performance without explicit reprogramming. Unlike traditional static models that rely on predefined rules or fixed training phases, adaptive AI systems operate in dynamic environments where uncertainty, variability, and incomplete information are inherent characteristics. The integration of computational intelligence methods, machine learning paradigms, reinforcement learning strategies, neural network architectures, and systems engineering principles forms the backbone of this adaptive framework.