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Da: Ria Christie Collections, Uxbridge, Regno Unito
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Da: Chiron Media, Wallingford, Regno Unito
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Da: GreatBookPricesUK, Woodford Green, Regno Unito
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Da: Revaluation Books, Exeter, Regno Unito
EUR 75,74
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Aggiungi al carrelloPaperback. Condizione: Brand New. 2014 edition. 188 pages. 8.25x5.75x0.50 inches. In Stock.
Lingua: Inglese
Editore: Springer Fachmedien Wiesbaden, 2014
ISBN 10: 3658049367 ISBN 13: 9783658049362
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 53,49
Quantità: 1 disponibili
Aggiungi al carrelloTaschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - Manipulating or grasping objects seems like a trivial task for humans, as these are motor skills of everyday life. Nevertheless, motor skills are not easy to learn for humans and this is also an active research topic in robotics. However, most solutions are optimized for industrial applications and, thus, few are plausible explanations for human learning. The fundamental challenge, that motivates Patrick Stalph, originates from the cognitive science: How do humans learn their motor skills The author makes a connection between robotics and cognitive sciences by analyzing motor skill learning using implementations that could be found in the human brain - at least to some extent. Therefore three suitable machine learning algorithms are selected - algorithms that are plausible from a cognitive viewpoint and feasible for the roboticist. The power and scalability of those algorithms is evaluated in theoretical simulations and more realistic scenarios with the iCub humanoid robot. Convincing results confirm the applicability of the approach, while the biological plausibility is discussed in retrospect.
Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 108,09
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Aggiungi al carrelloCondizione: As New. Unread book in perfect condition.
Lingua: Inglese
Editore: Springer Fachmedien Wiesbaden, 2014
ISBN 10: 3658049367 ISBN 13: 9783658049362
Da: preigu, Osnabrück, Germania
EUR 50,35
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Analysis and Design of Machine Learning Techniques | Evolutionary Solutions for Regression, Prediction, and Control Problems | Patrick Stalph | Taschenbuch | xix | Englisch | 2014 | Springer Fachmedien Wiesbaden | EAN 9783658049362 | Verantwortliche Person für die EU: Springer Vieweg in Springer Science + Business Media, Abraham-Lincoln-Str. 46, 65189 Wiesbaden, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Da: MusicMagpie, Stockport, Regno Unito
EUR 117,61
Quantità: 1 disponibili
Aggiungi al carrelloCondizione: Very Good. 1778675109. 5/13/2026 12:25:09 PM.
Da: Mispah books, Redhill, SURRE, Regno Unito
EUR 98,60
Quantità: 1 disponibili
Aggiungi al carrelloPaperback. Condizione: Like New. Like New. book.
Da: GreatBookPrices, Columbia, MD, U.S.A.
EUR 128,93
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Da: Buchpark, Trebbin, Germania
EUR 29,90
Quantità: 1 disponibili
Aggiungi al carrelloCondizione: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher | Manipulating or grasping objects seems like a trivial task for humans, as these are motor skills of everyday life. Nevertheless, motor skills are not easy to learn for humans and this is also an active research topic in robotics. However, most solutions are optimized for industrial applications and, thus, few are plausible explanations for human learning. The fundamental challenge, that motivates Patrick Stalph, originates from the cognitive science: How do humans learn their motor skills? The author makes a connection between robotics and cognitive sciences by analyzing motor skill learning using implementations that could be found in the human brain ¿ at least to some extent. Therefore three suitable machine learning algorithms are selected ¿ algorithms that are plausible from a cognitive viewpoint and feasible for the roboticist. The power and scalability of those algorithms is evaluated in theoretical simulations and more realistic scenarios with the iCub humanoid robot. Convincing results confirm the applicability of the approach, while the biological plausibility is discussed in retrospect.
Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing, 2014
ISBN 10: 3659638595 ISBN 13: 9783659638596
Da: preigu, Osnabrück, Germania
EUR 69,45
Quantità: 5 disponibili
Aggiungi al carrelloTaschenbuch. Condizione: Neu. Co-evolutionary and Reinforcement Learning Techniques in Computer Go | Some Techniques of Machine Learning Applied to Computer Go | Wester Zela Moraya | Taschenbuch | 276 S. | Englisch | 2014 | LAP LAMBERT Academic Publishing | EAN 9783659638596 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.
Da: Ria Christie Collections, Uxbridge, Regno Unito
EUR 186,64
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Aggiungi al carrelloCondizione: New. In.
Da: Ria Christie Collections, Uxbridge, Regno Unito
EUR 186,64
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Aggiungi al carrelloCondizione: New. In.
Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 186,63
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Da: GreatBookPrices, Columbia, MD, U.S.A.
EUR 204,15
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Aggiungi al carrelloCondizione: New.
Da: GreatBookPrices, Columbia, MD, U.S.A.
EUR 209,44
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Aggiungi al carrelloCondizione: As New. Unread book in perfect condition.
Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 210,25
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Aggiungi al carrelloCondizione: As New. Unread book in perfect condition.
Da: preigu, Osnabrück, Germania
EUR 166,90
Quantità: 5 disponibili
Aggiungi al carrelloTaschenbuch. Condizione: Neu. Evolutionary Machine Learning Techniques | Algorithms and Applications | Seyedali Mirjalili (u. a.) | Taschenbuch | Algorithms for Intelligent Systems | x | Englisch | 2020 | Springer | EAN 9789813299924 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Da: GreatBookPrices, Columbia, MD, U.S.A.
Condizione: New.
Condizione: New. pp. X, 286 72 illus., 55 illus. in color. 1st ed. 2020 edition NO-PA16APR2015-KAP.
Da: GreatBookPrices, Columbia, MD, U.S.A.
Condizione: As New. Unread book in perfect condition.
Lingua: Inglese
Editore: Springer Nature Singapore, Springer Nature Singapore, 2019
ISBN 10: 9813299894 ISBN 13: 9789813299894
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 198,81
Quantità: 1 disponibili
Aggiungi al carrelloBuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book provides an in-depth analysis of the current evolutionary machine learning techniques. Discussing the most highly regarded methods for classification, clustering, regression, and prediction, it includes techniques such as support vector machines, extreme learning machines, evolutionary feature selection, artificial neural networks including feed-forward neural networks, multi-layer perceptron, probabilistic neural networks, self-optimizing neural networks, radial basis function networks, recurrent neural networks, spiking neural networks, neuro-fuzzy networks, modular neural networks, physical neural networks, and deep neural networks.The book provides essential definitions, literature reviews, and the training algorithms for machine learning using classical and modern nature-inspired techniques. It also investigates the pros and cons of classical training algorithms. It features a range of proven and recent nature-inspired algorithms used to train different types of artificial neural networks, including genetic algorithm, ant colony optimization, particle swarm optimization, grey wolf optimizer, whale optimization algorithm, ant lion optimizer, moth flame algorithm, dragonfly algorithm, salp swarm algorithm, multi-verse optimizer, and sine cosine algorithm. The book also covers applications of the improved artificial neural networks to solve classification, clustering, prediction and regression problems in diverse fields.
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 201,36
Quantità: 1 disponibili
Aggiungi al carrelloTaschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book provides an in-depth analysis of the current evolutionary machine learning techniques. Discussing the most highly regarded methods for classification, clustering, regression, and prediction, it includes techniques such as support vector machines, extreme learning machines, evolutionary feature selection, artificial neural networks including feed-forward neural networks, multi-layer perceptron, probabilistic neural networks, self-optimizing neural networks, radial basis function networks, recurrent neural networks, spiking neural networks, neuro-fuzzy networks, modular neural networks, physical neural networks, and deep neural networks.The book provides essential definitions, literature reviews, and the training algorithms for machine learning using classical and modern nature-inspired techniques. It also investigates the pros and cons of classical training algorithms. It features a range of proven and recent nature-inspired algorithms used to train different types of artificial neural networks, including genetic algorithm, ant colony optimization, particle swarm optimization, grey wolf optimizer, whale optimization algorithm, ant lion optimizer, moth flame algorithm, dragonfly algorithm, salp swarm algorithm, multi-verse optimizer, and sine cosine algorithm. The book also covers applications of the improved artificial neural networks to solve classification, clustering, prediction and regression problems in diverse fields.
Lingua: Inglese
Editore: Springer Verlag, Singapore, Singapore, 2024
ISBN 10: 9819997178 ISBN 13: 9789819997176
Da: Grand Eagle Retail, Bensenville, IL, U.S.A.
Hardcover. Condizione: new. Hardcover. This book delves into practical implementation of evolutionary and metaheuristic algorithms to advance the capacity of machine learning. The readers can gain insight into the capabilities of data-driven evolutionary optimization in materials mechanics, and optimize your learning algorithms for maximum efficiency. Or unlock the strategies behind hyperparameter optimization to enhance your transfer learning algorithms, yielding remarkable outcomes. Or embark on an illuminating journey through evolutionary techniques designed for constructing deep-learning frameworks. The book also introduces an intelligent RPL attack detection system tailored for IoT networks. Explore a promising avenue of optimization by fusing Particle Swarm Optimization with Reinforcement Learning. It uncovers the indispensable role of metaheuristics in supervised machine learning algorithms. Ultimately, this book bridges the realms of evolutionary dynamic optimization andmachine learning, paving the way for pioneering innovations in the field. This book delves into practical implementation of evolutionary and metaheuristic algorithms to advance the capacity of machine learning. The readers can gain insight into the capabilities of data-driven evolutionary optimization in materials mechanics, and optimize your learning algorithms for maximum efficiency. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Da: preigu, Osnabrück, Germania
EUR 202,80
Quantità: 5 disponibili
Aggiungi al carrelloTaschenbuch. Condizione: Neu. Advanced Machine Learning with Evolutionary and Metaheuristic Techniques | Jayaraman Valadi (u. a.) | Taschenbuch | Computational Intelligence Methods and Applications | x | Englisch | 2025 | Springer | EAN 9789819997206 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Da: Revaluation Books, Exeter, Regno Unito
EUR 270,51
Quantità: 2 disponibili
Aggiungi al carrelloPaperback. Condizione: Brand New. 296 pages. 9.25x6.10x0.94 inches. In Stock.
Lingua: Inglese
Editore: Springer-Verlag New York Inc, 2019
ISBN 10: 9813299894 ISBN 13: 9789813299894
Da: Revaluation Books, Exeter, Regno Unito
EUR 272,47
Quantità: 2 disponibili
Aggiungi al carrelloHardcover. Condizione: Brand New. 298 pages. 9.25x6.10x0.87 inches. In Stock.
Condizione: New.