In recent years there has been increased interest in developing computational and mathematical models of learning and adaptation. Computational Neuroscience for Advancing Artificial Intelligence: Models, Methods and Applications captures the latest research in this area, providing a learning theorists with a mathematically sound framework within which evaluate their models. The significance of this book lies in its theoretical advances, which are grounded in an understanding of computational and biological learning. The approach taken moves the entire field closer to a watershed moment of learning models, through the interaction of computer science, psychology and neurobiology.
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Computational Neuroscience for Advancing Artificial Intelligence: Models, Methods and Applications captures the latest research in this area, providing a learning theorists with a mathematically sound framework within which evaluate their models. The significance of this book lies in its theoretical advances, which are grounded in an understanding of computational and biological learning. The approach taken moves the entire field closer to a watershed moment of learning models, through the interaction of computer science, psychology and neurobiology.
This book argues that computational models in behavioral neuroscience must be taken with caution, and advocates for the study of mathematical models of existing theories as complementary to neuro-psychological models and computational models -- Provided by publisher.
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Zustand: New. In. Artikel-Nr. ria9781609600211_new
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