Learning Robots, Andreas Birk; John Demiris

Автор: Juan Andrade Cetto; Alberto Sanfeliu
Название: Environment Learning for Indoor Mobile Robots
ISBN: 3642069312 ISBN-13(EAN): 9783642069314
Издательство: Springer
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Цена: 113180.00 T
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Описание: This monograph covers theoretical aspects of simultaneous localization and map building for mobile robots. One of the most relevant topics covered in this monograph is the theoretical formalism of partial observability in SLAM.

Автор: Todd Hester
Название: TEXPLORE: Temporal Difference Reinforcement Learning for Robots and Time-Constrained Domains
ISBN: 3319011677 ISBN-13(EAN): 9783319011677
Издательство: Springer
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Цена: 130610.00 T
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Описание: This book presents and develops new reinforcement learning methods that enable fast and robust learning on robots in real-time. It presents a novel model-based reinforcement learning algorithm.

Автор: Todd Hester
Название: TEXPLORE: Temporal Difference Reinforcement Learning for Robots and Time-Constrained Domains
ISBN: 3319375105 ISBN-13(EAN): 9783319375106
Издательство: Springer
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Цена: 104480.00 T
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Описание: This book presents and develops new reinforcement learning methods that enable fast and robust learning on robots in real-time. It presents a novel model-based reinforcement learning algorithm.

Автор: Hastie
Название: Statistical Learning with Sparsity
ISBN: 1498712169 ISBN-13(EAN): 9781498712163
Издательство: Taylor&Francis
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Цена: 112290.00 T
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Описание:

Discover New Methods for Dealing with High-Dimensional Data

A sparse statistical model has only a small number of nonzero parameters or weights; therefore, it is much easier to estimate and interpret than a dense model. Statistical Learning with Sparsity: The Lasso and Generalizations presents methods that exploit sparsity to help recover the underlying signal in a set of data.

Top experts in this rapidly evolving field, the authors describe the lasso for linear regression and a simple coordinate descent algorithm for its computation. They discuss the application of ℓ1 penalties to generalized linear models and support vector machines, cover generalized penalties such as the elastic net and group lasso, and review numerical methods for optimization. They also present statistical inference methods for fitted (lasso) models, including the bootstrap, Bayesian methods, and recently developed approaches. In addition, the book examines matrix decomposition, sparse multivariate analysis, graphical models, and compressed sensing. It concludes with a survey of theoretical results for the lasso.

In this age of big data, the number of features measured on a person or object can be large and might be larger than the number of observations. This book shows how the sparsity assumption allows us to tackle these problems and extract useful and reproducible patterns from big datasets. Data analysts, computer scientists, and theorists will appreciate this thorough and up-to-date treatment of sparse statistical modeling.

Автор: Nehaniv
Название: Imitation and Social Learning in Robots, Humans and Animals
ISBN: 0521108632 ISBN-13(EAN): 9780521108638
Издательство: Cambridge Academ
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Цена: 57030.00 T
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Описание: This book studies models and mechanisms of social matching behaviour and marks an important step towards the development of an interdisciplinary research field, consolidating and providing a valuable reference for the increasing number of researchers in the field of imitation and social learning in robots, humans and animals.

Автор: J?rgen Sturm
Название: Approaches to Probabilistic Model Learning for Mobile Manipulation Robots
ISBN: 3642371590 ISBN-13(EAN): 9783642371592
Издательство: Springer
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Цена: 139310.00 T
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Описание: This book presents novel learning techniques that enable mobile platforms with one or more robotic manipulators to autonomously adapt to new or changing situations.

Автор: Olivier Sigaud; Jan Peters
Название: From Motor Learning to Interaction Learning in Robots
ISBN: 3642262325 ISBN-13(EAN): 9783642262326
Издательство: Springer
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Цена: 186330.00 T
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Описание: This book is largely based on the successful workshop "From motor to interaction learning in robots" held at the IEEE/RSJ International Conference on Intelligent Robot Systems. It presents recent research in motor learning and interaction learning in robots.

Автор: Ceceri Kathy
Название: Making Simple Robots: Exploring Cutting-Edge Robotics with Everyday Stuff
ISBN: 1457183633 ISBN-13(EAN): 9781457183638
Издательство: Wiley
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Цена: 21110.00 T
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Описание: Making Simple Robots is based on one idea: Anybody can build a robot! That includes kids, English majors, school teachers, and grandparents.

Автор: Olivier Sigaud; Jan Peters
Название: From Motor Learning to Interaction Learning in Robots
ISBN: 3642051804 ISBN-13(EAN): 9783642051807
Издательство: Springer
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Цена: 278580.00 T
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Описание: This book is largely based on the successful workshop "From motor to interaction learning in robots" held at the IEEE/RSJ International Conference on Intelligent Robot Systems. It presents recent research in motor learning and interaction learning in robots.

Название: Frontiers in Data Science
ISBN: 1498799329 ISBN-13(EAN): 9781498799324
Издательство: Taylor&Francis
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Цена: 127600.00 T
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Описание: Frontiers in Data Science deals with philosophical and practical results in Data Science. A broad definition of Data Science describes the process of analyzing data to transform data into insights. This also involves asking philosophical, legal and social questions in the context of data generation and analysis.

Автор: Bir Bhanu; Ajay Kumar
Название: Deep Learning for Biometrics
ISBN: 3319616560 ISBN-13(EAN): 9783319616568
Издательство: Springer
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Цена: 130430.00 T
Наличие на складе: Невозможна поставка.
Описание: Issues of biometrics security are also examined.Topics and features: addresses the application of deep learning to enhance the performance of biometrics identification across a wide range of different biometrics modalities;

Автор: J?rgen Sturm
Название: Approaches to Probabilistic Model Learning for Mobile Manipulation Robots
ISBN: 3642437141 ISBN-13(EAN): 9783642437144
Издательство: Springer
Рейтинг:
Цена: 113180.00 T
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Описание: This book presents novel learning techniques that enable mobile platforms with one or more robotic manipulators to autonomously adapt to new or changing situations.