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Statistical Reinforcement Learning

field, Statistical Reinforcement Learning: Modern Machine Learning Approaches presents fundamental concepts and practical algorithms;

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Statistical Reinforcement Learning

field, Statistical Reinforcement Learning: Modern Machine Learning Approaches presents fundamental concepts and practical algorithms;

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Reinforcement Learning

Master reinforcement learning, a popular area of machine learning, starting with the basics: discover how agents and the environment evolve;

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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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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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An Introduction to Machine Learning

models, and a much more detailed treatment of reinforcement learning. The book is written in an easy-to-understand manner with many examples and;

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Inductive Logic Programming

areas of learning in logic, relational learning, relational data mining, statistical relational learning, multi-relational data mining;

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Supervised Reinforcement Learning

Supervised Reinforcement Learning is een boek van Karla Conn;

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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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Reinforcement Learning

Reinforcement learning encompasses both a science of adaptive behavior of rational beings in uncertain environments and a computational;

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Algorithmic Learning Theory

organized in topical sections named: error bounds, sample compression schemes; statistical learning, theory, evolvability; exact and interactive;

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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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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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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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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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Motivated Reinforcement Learning

extend reinforcement learning to adaptive, multitask learning in complex, dynamic environments - the goal being to understand how machines can;

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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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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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Introduction to Machine Learning

, multivariate analysis, hidden Markov models, reinforcement learning, kernel machines, graphical models, Bayesian estimation, and statistical testing;

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Reinforcement and Systemic Machine Learning for Decision Making

Reinforcement and Systemic Machine Learning for Decision Making explores a newer and growing avenue of machine learning algorithm in the;

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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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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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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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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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Handbook of Reinforcement Learning and Control

This handbook presents state-of-the-art research in reinforcement learning, focusing on its applications in the control and game theory;

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Reinforcement Learning

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