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Reinforcement Learning, second edition
The significantly expanded and updated new edition of a widely used text on reinforcement learning, one of the most active research areas in artificial intelligence. Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives while interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the field's key ideas and algorithms. This second edition has been significantly expanded and updated, presenting new topics and updating coverage of other topics. Like the fir...
Reinforcement Learning, second edition
The significantly expanded and updated new edition of a widely used text on reinforcement learning, one of the most active research areas in artificial intelligence. Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives while interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the field's key ideas and algorithms. This second edition has been significantly expanded and updated, presenting new topics and updating coverage of other topics. Like the fir...
Neural Networks for Control
Neural Networks for Control brings together examples of all the most important paradigms for the application of neural networks to robotics and control. Primarily concerned with engineering problems and approaches to their solution through neurocomputing systems, the book is divided into three sections: general principles, motion control, and applications domains (with evaluations of the possible applications by experts in the applications areas.) Special emphasis is placed on designs based on optimization or reinforcement, which will become increasingly important as researchers address more complex engineering challenges or real biological-control problems.A Bradford Book. Neural Network Modeling and Connectionism series
Richard III's Books
Richard III, the most notorious and most discussed of English kings, was also unusual among his contemporaries in regularly signing his books. This characteristic, among others, has enabled Anne Sutton and Livia Visser-Fuchs to reconstruct his library, and link it to the culture and reading habits of his generation. The books of Richard III are typical of what was available to and popular with the medieval reader – religion, chivalry, history, genealogy, advice on how to govern, romance and prophecy – and allow us to draw an interesting overview of fifteenth-century opinions. Each type of book is examined on its own terms and then related to the known preoccupations of Richard himself, his associates and to the political practices of his time. Containing valuable biographical material, insights into the history and politics of the later fifteenth century, and much detail on late medieval piety and other important aspects of contemporary culture, this fully illustrated survey has wide-ranging significance for all who study the history and literature of the medieval period.
Deep Reinforcement Learning Hands-On
Maxim Lapan delivers intuitive explanations and insights into complex reinforcement learning (RL) concepts, starting from the basics of RL on simple environments and tasks to modern, state-of-the-art methods Purchase of the print or Kindle book includes a free PDF eBook Key Features Learn with concise explanations, modern libraries, and diverse applications from games to stock trading and web navigation Develop deep RL models, improve their stability, and efficiently solve complex environments New content on RL from human feedback (RLHF), MuZero, and transformers Book Description Start your journey into reinforcement learning (RL) and reward yourself with the third edition of Deep Reinforcem...
The Stress Code
‘One of the greatest lessons Richard has taught me is the immense power of positive habits in shaping realities. His approach to stress management and resilience has completely transformed my life.’ - NATASHA SIDERIS, Founder and CEO of the Tashas group Stress impacts all facets of our lives and has devastating effects on the global economy, including reduced productivity and the burden it places on healthcare systems. Decades of research show that chronic stress severely compromises our physical and mental health. More recently, it has been revealed that stress can destabilise our DNA and affect our genetic integrity. This promotes many of the diseases that societies are currently grapp...
Algorithms for Reinforcement Learning
Reinforcement learning is a learning paradigm concerned with learning to control a system so as to maximize a numerical performance measure that expresses a long-term objective. What distinguishes reinforcement learning from supervised learning is that only partial feedback is given to the learner about the learner's predictions. Further, the predictions may have long term effects through influencing the future state of the controlled system. Thus, time plays a special role. The goal in reinforcement learning is to develop efficient learning algorithms, as well as to understand the algorithms' merits and limitations. Reinforcement learning is of great interest because of the large number of ...
Talking Nets
Surprising tales from the scientists who first learned how to use computers to understand the workings of the human brain. Since World War II, a group of scientists has been attempting to understand the human nervous system and to build computer systems that emulate the brain's abilities. Many of the early workers in this field of neural networks came from cybernetics; others came from neuroscience, physics, electrical engineering, mathematics, psychology, even economics. In this collection of interviews, those who helped to shape the field share their childhood memories, their influences, how they became interested in neural networks, and what they see as its future. The subjects tell stori...
Stressproof
The world faces a ‘giant storm’ of stress and burnout that is exacerbated in the context of the COVID-19 pandemic and the Fourth Industrial Revolution. Learning how to navigate the world going forward is something that everyone has to do. How can leaders help themselves, their employees and their businesses to thrive in the face of these and other challenges? Stressproof speaks to the crisis currently facing the professional landscape. It outlines the conundrum of stress and its performance advantage versus its destructiveness; and it focuses on the stress-related challenges facing decision makers in the world of business today. Practical, insightful and based on case studies and real-world examples, Stressproof provides a game-changing action plan to help managers, leaders and those who are making decisions.
Reinforcement Learning
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 exciting development avoids constraints found in traditional machine learning (ML) algorithms. This practical book shows data science and AI professionals how to learn by reinforcement and enable a machine to learn by itself. Author Phil Winder of Winder Research covers everything from basic building blocks to state-of-the-art practices. You'll explore the current state of RL, focus on industrial applications, learn numerous algorithms, and benefit from dedicated chapters on deploying RL solutions to product...
