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Reinforcement learning for cyber-physical systems, Li, Chong Qiu, Meikang


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Автор: Li, Chong Qiu, Meikang
Название:  Reinforcement learning for cyber-physical systems
ISBN: 9780367656638
Издательство: Taylor&Francis
Классификация:



ISBN-10: 0367656639
Обложка/Формат: Paperback
Страницы: 238
Вес: 0.40 кг.
Дата издания: 30.09.2020
Язык: English
Размер: 164 x 232 x 21
Читательская аудитория: Postgraduate, research & scholarly
Подзаголовок: With cybersecurity case studies
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Поставляется из: Европейский союз
Описание: This book introduces reinforcement learning, and provides novel ideas and use cases to demonstrate the benefits of using reinforcement learning for Cyber Physical Systems. Two important case studies on applying reinforcement learning to cybersecurity problems are included.


Hands-On Reinforcement Learning for Games

Автор: Lanham Micheal
Название: Hands-On Reinforcement Learning for Games
ISBN: 1839214937 ISBN-13(EAN): 9781839214936
Издательство: Неизвестно
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Цена: 8091.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: The AI revolution is here and it is embracing games. Game developers are being challenged to enlist cutting edge AI as part of their games. In this book, you will look at the journey of building capable AI using reinforcement learning algorithms and techniques. You will learn to solve complex tasks and build next-generation games using a ...

Statistical Reinforcement Learning

Автор: Sugiyama
Название: Statistical Reinforcement Learning
ISBN: 1439856893 ISBN-13(EAN): 9781439856895
Издательство: Taylor&Francis
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Цена: 13014.00 р.
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Описание:

Reinforcement learning is a mathematical framework for developing computer agents that can learn an optimal behavior by relating generic reward signals with its past actions. With numerous successful applications in business intelligence, plant control, and gaming, the RL framework is ideal for decision making in unknown environments with large amounts of data.

Supplying an up-to-date and accessible introduction to the field, Statistical Reinforcement Learning: Modern Machine Learning Approaches presents fundamental concepts and practical algorithms of statistical reinforcement learning from the modern machine learning viewpoint. It covers various types of RL approaches, including model-based and model-free approaches, policy iteration, and policy search methods.

  • Covers the range of reinforcement learning algorithms from a modern perspective
  • Lays out the associated optimization problems for each reinforcement learning scenario covered
  • Provides thought-provoking statistical treatment of reinforcement learning algorithms

The book covers approaches recently introduced in the data mining and machine learning fields to provide a systematic bridge between RL and data mining/machine learning researchers. It presents state-of-the-art results, including dimensionality reduction in RL and risk-sensitive RL. Numerous illustrative examples are included to help readers understand the intuition and usefulness of reinforcement learning techniques.

This book is an ideal resource for graduate-level students in computer science and applied statistics programs, as well as researchers and engineers in related fields.

TensorFlow 2 Reinforcement Learning Cookbook: Over 50 recipes to help you build, train, and deploy learning agents for real-world applications

Автор: Palanisamy Praveen
Название: TensorFlow 2 Reinforcement Learning Cookbook: Over 50 recipes to help you build, train, and deploy learning agents for real-world applications
ISBN: 183898254X ISBN-13(EAN): 9781838982546
Издательство: Неизвестно
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Цена: 9010.00 р.
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Описание: This cookbook will help you to gain a solid understanding of deep reinforcement learning (RL) algorithms with the help of concise, easy-to-follow implementations from scratch. You`ll learn how to implement these algorithms with minimal code and develop AI applications to solve real-world and business problems using RL.

Reinforcement learning

Автор: Sutton, Richard S. Barto, Andrew G.
Название: Reinforcement learning
ISBN: 0262193981 ISBN-13(EAN): 9780262193986
Издательство: MIT Press
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Цена: 10040.00 р.
Наличие на складе: Нет в наличии.

Описание: An account of key ideas and algorithms in reinforcement learning. The discussion ranges from the history of the field`s intellectual foundations to recent developments and applications. Areas studied include reinforcement learning problems in terms of Markov decision problems and solution methods.

Reinforcement Learning

Автор: Richard S. Sutton
Название: Reinforcement Learning
ISBN: 0792392345 ISBN-13(EAN): 9780792392347
Издательство: Springer
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Цена: 30606.00 р.
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Описание: Reinforcement learning is the learning of mapping from situations to actions so as to maximize a scalar reward or reinforcement signal. The learner is not told which action to take but instead must discover which actions yield the highest reward. This book contains research data on the subject.

Reinforcement Learning for Cyber-Physical Systems with Cybersecurity Case Studies

Автор: Li, Chong
Название: Reinforcement Learning for Cyber-Physical Systems with Cybersecurity Case Studies
ISBN: 1138543535 ISBN-13(EAN): 9781138543539
Издательство: Taylor&Francis
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Цена: 12707.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This book introduces reinforcement learning, and provides novel ideas and use cases to demonstrate the benefits of using reinforcement learning for Cyber Physical Systems. Two important case studies on applying reinforcement learning to cybersecurity problems are included.

Reinforcement learning algorithms with python

Автор: Lonza, Andrea
Название: Reinforcement learning algorithms with python
ISBN: 1789131111 ISBN-13(EAN): 9781789131116
Издательство: Неизвестно
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Цена: 7171.00 р.
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Описание: With this book, you will understand the core concepts and techniques of reinforcement learning. You will take a look into each RL algorithm and will develop your own self-learning algorithms and models. You will optimize the algorithms for better precision, use high-speed actions and lower the risk of anomalies in your applications.

Hands-on reinforcement learning with python -

Автор: Ravichandiran, Sudharsan
Название: Hands-on reinforcement learning with python -
ISBN: 1839210680 ISBN-13(EAN): 9781839210686
Издательство: Неизвестно
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Цена: 9010.00 р.
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Описание: Deep Reinforcement Learning with Python - Second Edition will help you learn reinforcement learning algorithms, techniques and architectures - including deep reinforcement learning - from scratch. This new edition is an extensive update of the original, reflecting the state-of-the-art latest thinking in reinforcement learning.

Reinforcement Learning with Tensorflow

Автор: Dutta Sayon
Название: Reinforcement Learning with Tensorflow
ISBN: 1788835727 ISBN-13(EAN): 9781788835725
Издательство: Неизвестно
Цена: 10114.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: Reinforcement learning allows you to develop intelligent, self-learning systems. This book shows you how to put the concepts of Reinforcement Learning to train efficient models.You will use popular reinforcement learning algorithms to implement use-cases in image processing and NLP, by combining the power of TensorFlow and OpenAI Gym.

Deep Reinforcement Learning Hands-On - Second Edition

Автор: Lapan Maxim
Название: Deep Reinforcement Learning Hands-On - Second Edition
ISBN: 1838826998 ISBN-13(EAN): 9781838826994
Издательство: Неизвестно
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Цена: 14712.00 р.
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Описание: With six new chapters, Deep Reinforcement Learning Hands-On Second edition is completely updated and expanded with the very latest reinforcement learning (RL) tools and techniques, providing you with an introduction to RL, as well as the hands-on ability to code intelligent learning agents to perform a range of practical tasks.

Machine Learning for Cyber Physical Systems

Автор: Oliver Niggemann; J?rgen Beyerer
Название: Machine Learning for Cyber Physical Systems
ISBN: 3662488361 ISBN-13(EAN): 9783662488362
Издательство: Springer
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Цена: 19591.00 р.
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Описание: Development of a Cyber-Physical System based on selective dynamic Gaussian naive Bayes model for a self-predict laser surface heat treatment processcontrol.- Evidence Grid Based Information Fusion for Semantic Classifiers in Dynamic Sensor Networks.- Forecasting Cellular Connectivity for Cyber-Physical Systems: A Machine Learning Approach.- Towards Optimized Machine Operations by Cloud Integrated Condition Estimation.- Prognostics Health Management System based on Hybrid Model to Predict Failures of a Planetary Gear Transmission.- Evaluation of Model-Based Condition Monitoring Systems in Industrial Application Cases.- Towards a novel learning assistant for networked automation systems.- Effcient Image Processing System for an Industrial Machine Learning Task.- Efficient engineering in special purpose machinery through automated control code synthesis based on a functional categorisation.- Geo-Distributed Analytics for the Internet of Things.- Implementation and Comparison of Cluster-Based PSO Extensions in Hybrid Settings with Efficient Approximation.- Machine-specifc Approach for Automatic Classifcation of Cutting Process Efficiency.- Meta-analysis of Maintenance Knowledge Assets Towards Predictive Cost Controlling of Cyber Physical Production Systems.- Towards Autonomously Navigating and Cooperating Vehicles in Cyber-Physical Production Systems.

Python Reinforcement Learning Projects

Автор: Saito Sean, Wenzhuo Yang, Shanmugamani Rajalingappaa
Название: Python Reinforcement Learning Projects
ISBN: 1788991613 ISBN-13(EAN): 9781788991612
Издательство: Неизвестно
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Цена: 9010.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: Python Reinforcement Learning Projects brings various aspects and methodologies of RL using 8 real-world projects that explore RL and will have hands-on experience with real data and artificial intelligence problems. You will learn to build self-learning models using sophisticated techniques like Q-learning, Markov models and Monte-Carlo process.


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