Cognitive Semantics of Artificial Intelligence : A New Perspective / by Alexander Raikov.
By: Raikov, Alexander, autor
Material type:
E-bookSeries: (SpringerBriefs in Computational Intelligence, 2625-3704); (Intelligent Technologies and Robotics (SpringerNature-42732)); (Intelligent Technologies and Robotics (R0) (SpringerNature-43728)).Publisher: Singapore : Springer International Pulishing, 2021Edition: First edition 2021.Description: 1 recurso en línea (XVII, 128 páginas) : 16 ilustraciones, 7 ilustraciones a color.ISBN: 9789813367500.Subject: Inteligencia artificial
| Item type | Current library | Call number | Status | Date due | Barcode | Item holds | |
|---|---|---|---|---|---|---|---|
LIBRO-E NO PRÉSTAMO
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Madrid Digital Acceso Electrónico (UEM) | Q342 2021 EB (Browse shelf(Opens below)) | Acceso electrónico | eBook.14032068 |
History of Knowledge -- Philosophy of Knowledge -- Nonlogic Thought -- Hidden Consciousness -- Formalized Semantics -- Cosmomicrophysical Thinking -- Nonlocal Brainstorming -- Purposeful Creativity -- Cognitive Structures -- Quantum Semantics -- Optical Semantics -- Wave of Consciousness -- Entanglement of Thought -- Thought Event -- Thought Boosts -- Purposeful Chaos -- Dissipative Thought -- Purposefulness of Thought -- Small Impacts -- Light Thought -- Quantization of Thought -- Thought Interferometry -- Architecture of AI Semantics -- Applications.
This book addresses the issue of cognitive semantics' aspects that cannot be represented by traditional digital and logical means. The problem of creating cognitive semantics can be resolved in an indirect way. The electromagnetic waves, quantum fields, beam of light, chaos control, relativistic theory, cosmic string recognition, category theory, group theory, and so on can be used for this aim. Since the term artificial intelligence (AI) appeared, various versions of logic have been created; many heuristics for neural networks deep learning have been made; new nature-like algorithms have been suggested. At the same time, the initial digital, logical, and neural network principles of representation of knowledge in AI systems have not changed a lot. The researches of these aspects of cognitive semantics of AI are based on the author's convergent methodology, which provides the necessary conditions for purposeful and sustainable convergence of decision-making.
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