Motivated Reinforcement Learning, Kathryn E. Merrick; Mary Lou Maher
Автор: Rieser, Verena Название: Reinforcement Learning for Adaptive Dialogue Systems ISBN: 3642249418 ISBN-13(EAN): 9783642249419 Издательство: Springer Рейтинг: Цена: 16769.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The past decade has seen a revolution in the field of spoken dialogue systems. As in other areas of Computer Science and Artificial Intelligence, data-driven methods are now being used to drive new methodologies for system development and evaluation. This book is a unique contribution to that ongoing change. A new methodology for developing spoken dialogue systems is described in detail. The journey starts and ends with human behaviour in interaction, and explores methods for learning from the data, for building simulation environments for training and testing systems, and for evaluating the results. The detailed material covers: Spoken and Multimodal dialogue systems, Wizard-of-Oz data collection, User Simulation methods, Reinforcement Learning, and Evaluation methodologies. The book is a research guide for students and researchers with a background in Computer Science, AI, or Machine Learning. It navigates through a detailed case study in data-driven methods for development and evaluation of spoken dialogue systems. Common challenges associated with this approach are discussed and example solutions are provided. This work provides insights, lessons, and inspiration for future research and development – not only for spoken dialogue systems in particular, but for data-driven approaches to human-machine interaction in general.
Автор: Shimon Whiteson Название: Adaptive Representations for Reinforcement Learning ISBN: 3642422314 ISBN-13(EAN): 9783642422317 Издательство: Springer Рейтинг: Цена: 15672.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Presenting the main results of new algorithms for reinforcement learning, this book also introduces a novel method for devising input representations as well as presenting a way to find a minimal set of features sufficient to describe the agent`s current state.
Автор: Lutz Frommberger Название: Qualitative Spatial Abstraction in Reinforcement Learning ISBN: 3642266002 ISBN-13(EAN): 9783642266003 Издательство: Springer Рейтинг: Цена: 16070.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Reinforcement learning has evolved to tackle domains that are yet to be fully understood, or are too complex for a closed description. In this book the author investigates whether suitable abstraction methods can overcome the discipline`s deficiencies.
Автор: Matthew Taylor Название: Transfer in Reinforcement Learning Domains ISBN: 3642018815 ISBN-13(EAN): 9783642018817 Издательство: Springer Рейтинг: Цена: 23757.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Reinforcement Learning Background.- Related Work.- Empirical Domains.- Value Function Transfer via Inter-Task Mappings.- Extending Transfer via Inter-Task Mappings.- Transfer between Different Reinforcement Learning Methods.- Learning Inter-Task Mappings.- Conclusion and Future Work.
Автор: Matthew Taylor Название: Transfer in Reinforcement Learning Domains ISBN: 3642101860 ISBN-13(EAN): 9783642101861 Издательство: Springer Рейтинг: Цена: 23757.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: In reinforcement learning (RL) problems, learning agents sequentially execute actions with the goal of maximizing a reward signal. This book provides an introduction to the RL transfer problem and discusses methods which demonstrate the promise of this exciting area of research.
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: Marco Wiering; Martijn van Otterlo Название: Reinforcement Learning ISBN: 364244685X ISBN-13(EAN): 9783642446856 Издательство: Springer Рейтинг: Цена: 32651.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book presents up-to-date information on the main contemporary sub-fields of reinforcement learning, including partially observable environments, hierarchical task decompositions, relational knowledge representation and predictive state representations.
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: Gianluca Baldassarre; Marco Mirolli Название: Intrinsically Motivated Learning in Natural and Artificial Systems ISBN: 3642442935 ISBN-13(EAN): 9783642442933 Издательство: Springer Рейтинг: Цена: 21661.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book presents the state of the art in research on intrinsically motivated learning and presents novel tools for research. It also identifies related scientific and technological open challenges as well as promising research directions.
Автор: Verena Rieser; Oliver Lemon Название: Reinforcement Learning for Adaptive Dialogue Systems ISBN: 3642439845 ISBN-13(EAN): 9783642439841 Издательство: Springer Рейтинг: Цена: 18167.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book contributes to progress in spoken dialogue systems with a new, data-driven methodology. Covers Spoken and Multimodal dialogue systems; Wizard-of-Oz data collection; User Simulation methods; Reinforcement Learning and Evaluation methodologies.
Автор: Christopher Gatti Название: Design of Experiments for Reinforcement Learning ISBN: 3319385518 ISBN-13(EAN): 9783319385518 Издательство: Springer Рейтинг: Цена: 15372.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This thesis takes an empirical approach to understanding of the behavior and interactions between the two main components of reinforcement learning: the learning algorithm and the functional representation of learned knowledge.
Автор: Seong-Whang Lee; Heinrich H. B?lthoff; Tomaso Pogg Название: Biologically Motivated Computer Vision ISBN: 3540675604 ISBN-13(EAN): 9783540675600 Издательство: Springer Рейтинг: Цена: 16769.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Constitutes 56 revised papers presented together with 8 invited papers divided in topical sections on segmentation, detection, and object recognition computational models in biologically motivated computer vision. The title is aimed at researchers of image processing and problem complexity.
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