Автор: Farsi, Milad, Название: Model-based reinforcement learning : ISBN: 111980857X ISBN-13(EAN): 9781119808572 Издательство: Wiley Рейтинг: Цена: 108770.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book is for researchers and students in statistics, data mining, computer science, machine learning, marketing and also practitioners who implement recommender systems. It provides an in-depth discussion of challenges encountered in deploying real-life large-scale systems and state-of-the-art solutions in personalization, explore/exploit, dimension reduction and multi-objective optimization.
Автор: Mohit Sewak Название: Deep Reinforcement Learning ISBN: 9811382840 ISBN-13(EAN): 9789811382840 Издательство: Springer Рейтинг: Цена: 121110.00 T Наличие на складе: Поставка под заказ. Описание: This book starts by presenting the basics of reinforcement learning using highly intuitive and easy-to-understand examples and applications, and then introduces the cutting-edge research advances that make reinforcement learning capable of out-performing most state-of-art systems, and even humans in a number of applications. The book not only equips readers with an understanding of multiple advanced and innovative algorithms, but also prepares them to implement systems such as those created by Google Deep Mind in actual code.This book is intended for readers who want to both understand and apply advanced concepts in a field that combines the best of two worlds – deep learning and reinforcement learning – to tap the potential of ‘advanced artificial intelligence’ for creating real-world applications and game-winning algorithms.
Автор: Vamvoudakis Kyriakos G., Wan Yan, Lewis Frank L. Название: Handbook of Reinforcement Learning and Control ISBN: 3030609898 ISBN-13(EAN): 9783030609894 Издательство: Springer Цена: 214280.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The Cognitive Dialogue: A New Architecture for Perception and Cognition.- Rooftop-Aware Emergency Landing Planning for Small Unmanned Aircraft Systems.- Quantum Reinforcement Learning in Changing Environment.- The Role of Thermodynamics in the Future Research Directions in Control and Learning.- Mixed Density Reinforcement Learning Methods for Approximate Dynamic Programming.- Analyzing and Mitigating Link-Flooding DoS Attacks Using Stackelberg Games and Adaptive Learning.- Learning and Decision Making for Complex Systems Subjected to Uncertainties: A Stochastic Distribution Control Approach.- Optimal Adaptive Control of Partially Unknown Linear Continuous-time Systems with Input and State Delay.- Gradient Methods Solve the Linear Quadratic Regulator Problem Exponentially Fast.- Architectures, Data Representations and Learning Algorithms: New Directions at the Confluence of Control and Learning.- Reinforcement Learning for Optimal Feedback Control and Multiplayer Games.- Fundamental Principles of Design for Reinforcement Learning Algorithms Course Titles.- Long-Term Impacts of Fair Machine Learning.- Learning-based Model Reduction for Partial Differential Equations with Applications to Thermo-Fluid Models' Identification, State Estimation, and Stabilization.- CESMA: Centralized Expert Supervises Multi-Agents, for Decentralization.- A Unified Framework for Reinforcement Learning and Sequential Decision Analytics.- Trading Utility and Uncertainty: Applying the Value of Information to Resolve the Exploration-Exploitation Dilemma in Reinforcement Learning.- Multi-Agent Reinforcement Learning: Recent Advances, Challenges, and Applications.- Reinforcement Learning Applications, An Industrial Perspective.- A Hybrid Dynamical Systems Perspective of Reinforcement Learning.- Bounded Rationality and Computability Issues in Learning, Perception, Decision-Making, and Games Panagiotis Tsiotras.- Mixed Modality Learning.- Computational Intelligence in Uncertainty Quantification for Learning Control and Games.- Reinforcement Learning Based Optimal Stabilization of Unknown Time Delay Systems Using State and Output Feedback.- Robust Autonomous Driving with Humans in the Loop.- Boundedly Rational Reinforcement Learning for Secure Control.
Автор: Yinyan Zhang; Shuai Li; Xuefeng Zhou Название: Deep Reinforcement Learning with Guaranteed Performance ISBN: 3030333833 ISBN-13(EAN): 9783030333836 Издательство: Springer Рейтинг: Цена: 121110.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book discusses methods and algorithms for the near-optimal adaptive control of nonlinear systems, including the corresponding theoretical analysis and simulative examples, and presents two innovative methods for the redundancy resolution of redundant manipulators with consideration of parameter uncertainty and periodic disturbances.It also reports on a series of systematic investigations on a near-optimal adaptive control method based on the Taylor expansion, neural networks, estimator design approaches, and the idea of sliding mode control, focusing on the tracking control problem of nonlinear systems under different scenarios. The book culminates with a presentation of two new redundancy resolution methods; one addresses adaptive kinematic control of redundant manipulators, and the other centers on the effect of periodic input disturbance on redundancy resolution.Each self-contained chapter is clearly written, making the book accessible to graduate students as well as academic and industrial researchers in the fields of adaptive and optimal control, robotics, and dynamic neural networks.
Автор: Lonza, Andrea Название: Reinforcement learning algorithms with python ISBN: 1789131111 ISBN-13(EAN): 9781789131116 Издательство: Неизвестно Рейтинг: Цена: 47810.00 T Наличие на складе: Есть у поставщика Поставка под заказ. 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.
Автор: Sutton, Richard S. Barto, Andrew G. Название: Reinforcement learning ISBN: 0262193981 ISBN-13(EAN): 9780262193986 Издательство: MIT Press Рейтинг: Цена: 66930.00 T 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.
Автор: de Ponteves Hadelin Название: AI Crash Course ISBN: 1838645357 ISBN-13(EAN): 9781838645359 Издательство: Неизвестно Рейтинг: Цена: 40450.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: AI legend Hadelin de Ponteves captures his proven AI training approach in a friendly, interactive, and hands-on tutorial book.
Автор: D Phil Winder Название: Reinforcement Learning: Industrial Applications of Intelligent Agents ISBN: 1098114833 ISBN-13(EAN): 9781098114831 Издательство: Wiley Рейтинг: Цена: 55960.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Reinforcement learning (RL) will deliver one of the biggest breakthroughs in AI over the next decade, enabling algorithms to learn from their environment to achieve arbitrary goals. This practical book shows data science and AI professionals how to perform the reinforcement process that allows a machine to learn by itself.
Автор: Kathryn E. Merrick; Mary Lou Maher Название: Motivated Reinforcement Learning ISBN: 364210035X ISBN-13(EAN): 9783642100352 Издательство: Springer Рейтинг: Цена: 121110.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book covers the design, application and evaluation of computational models of motivation in reinforcement learning. The performance of these models is demonstrated by applications in simulated game scenarios and a live, open-ended, virtual world.
Автор: Chinnamgari Sunil Kumar Название: R Machine Learning Projects ISBN: 1789807948 ISBN-13(EAN): 9781789807943 Издательство: Неизвестно Рейтинг: Цена: 53940.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The purpose of the book is to help a machine learning practitioner gets hands-on experience in working with real-world data and apply modern machine learning algorithms. You will learn to implement each algorithm to a specific industry problem. It covers projects involving both supervised as well as unsupervised learning approaches.
Автор: Belousov Boris, Abdulsamad Hany, Klink Pascal Название: Reinforcement Learning Algorithms: Analysis and Applications ISBN: 3030411877 ISBN-13(EAN): 9783030411879 Издательство: Springer Цена: 130430.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book reviews research developments in diverse areas of reinforcement learning such as model-free actor-critic methods, model-based learning and control, information geometry of policy searches, reward design, and exploration in biology and the behavioral sciences.
Автор: Kajal Singh, Matthew E. Taylor, Philip Osborne Название: Applying Reinforcement Learning on Real-World Data with Practical Examples in Python ISBN: 1636393446 ISBN-13(EAN): 9781636393445 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 45270.00 T Наличие на складе: Нет в наличии. Описание: Reinforcement learning is a powerful tool in artificial intelligence in which virtual or physical agents learn to optimize their decision making to achieve long-term goals. This book shows how reinforcement learning can be adopted in different situations, including robot control, stock trading, supply chain optimization, and plant control.
Казахстан, 010000 г. Астана, проспект Туран 43/5, НП2 (офис 2) ТОО "Логобук" Тел:+7 707 857-29-98 ,+7(7172) 65-23-70 www.logobook.kz
