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Hands-On Reinforcement Learning with Python

A hands-on guide enriched with examples to master deep reinforcement learning algorithms with Python Key Features Your entry point into the;

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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;

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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;

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Python Reinforcement Learning Projects

Implement state-of-the-art deep reinforcement learning algorithms using Python and its powerful libraries Key Features Implement Q-learning;

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Applied Reinforcement Learning with Python

Delve into the world of reinforcement learning algorithms and apply them to different use-cases via Python. This book covers important;

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Deep Reinforcement Learning with Python

Deep reinforcement learning is a fast-growing discipline that is making a significant impact in fields of autonomous vehicles, robotics;

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Statistical Reinforcement Learning

Reinforcement learning is a mathematical framework for developing computer agents that can learn an optimal behavior by relating generic;

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Statistical Reinforcement Learning

Reinforcement learning is a mathematical framework for developing computer agents that can learn an optimal behavior by relating generic;

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Reinforcement Learning for Finance

This book introduces reinforcement learning with mathematical theory and practical examples from quantitative finance using the TensorFlow;

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Reinforcement Learning Algorithms

This book reviews research developments in diverse areas of reinforcement learning such as model-free actor-critic methods, model-based;

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Zai:Deep Reinforcement Learning i_p

cannot. Deep Reinforcement Learning in Action teaches you the fundamental concepts and terminology of deep reinforcement learning, along;

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TensorFlow 2 Reinforcement Learning Cookbook

Discover recipes for developing AI applications to solve a variety of real-world business problems using reinforcement learning Key;

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Reinforcement Learning Algorithms with Python

, and deploy advanced reinforcement learning algorithms to solve a variety of tasks Understand and develop model-free and model-based algorithms;

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Reinforcement Learning with Hybrid Quantum Approximation in the NISQ Context

This book explores the combination of Reinforcement Learning and Quantum Computing in the light of complex attacker-defender scenarios;

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Python Reinforcement Learning

Apply modern reinforcement learning and deep reinforcement learning methods using Python and its powerful libraries Key Features Your entry;

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Reinforcement Learning

The significantly expanded and updated new edition of a widely used text on reinforcement learning, one of the most active research areas;

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Reinforcement Learning

Richard Sutton and Andrew Barto provide a clear and simple account of the key ideas and algorithms of reinforcement learning. Their;

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Reinforcement Learning

Reinforcement learning (RL) will deliver one of the biggest breakthroughs in AI over the next decade, enabling algorithms to learn from;

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Foundations of Deep Reinforcement Learning

The Contemporary Introduction to Deep Reinforcement Learning that Combines Theory and Practice Deep reinforcement learning (deep RL;

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Reinforcement Learning From Scratch

spectacular reinforcement learning algorithms work? With easy-to-understand explanations and clear examples in Java and Greenfoot, you can;

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Hands-On Reinforcement Learning for Games

Explore reinforcement learning (RL) techniques to build cutting-edge games using Python libraries such as PyTorch, OpenAI Gym, and;

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Reinforcement Learning for Cyber-Physical Systems

Reinforcement Learning for Cyber-Physical Systems: with Cybersecurity Case Studies was inspired by recent developments in the fields;

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Reinforcement Learning for Cyber-Physical Systems

Reinforcement Learning for Cyber-Physical Systems: with Cybersecurity Case Studies was inspired by recent developments in the fields;

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Grokking Deep Reinforcement Learning

Written for developers with some understanding of deep learning algorithms. Experience with reinforcement learning is not required;

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The The Reinforcement Learning Workshop

Start with the basics of reinforcement learning and explore deep learning concepts such as deep Q-learning, deep recurrent Q-networks, and;

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Neural Fuzzy Control Systems With Structure And Parameter Learning

applications, exact training data may be expensive or even impossible to get. To solve this reinforcement learning problem for real-world applications;

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Human-Robot Interaction Control Using Reinforcemen t Learning

, model-free and reinforcement learning controllers. The book begins with a brief introduction to state-of-the-art human-robot interaction control;

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