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Reinforcement Learning of Bimanual Robot Skills

This book tackles all the stages and mechanisms involved in the learning of manipulation tasks by bimanual robots in unstructured settings;

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Reinforcement Learning of Bimanual Robot Skills

This book tackles all the stages and mechanisms involved in the learning of manipulation tasks by bimanual robots in unstructured settings;

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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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Advanced Bimanual Manipulation

Dexterous and autonomous manipulation is a key technology for the personal and service robots of the future. Advances in Bimanual;

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Hands-On ROS for Robotics Programming

produce adaptive responses Apply reinforcement learning to allow your robot to learn by trial and error Implement deep learning to enable your;

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Machine Learning based Natural Scene Recognition for Mobile Robot Localization i

feature representations and decision-making using reinforcement learning, laying the groundwork for future advances in mobile robot navigation;

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Recent Advances in Robot Learning

programming to reinforcement learning, is being applied to many subproblems in robot perception and control, often with objectives as diverse as;

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MultiAgent Coordination

Coordination: A Reinforcement Learning Approach delivers a comprehensive, insightful, and unique treatment of the development of multi-robot;

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Robot Shaping

environment are unpredictable, and the robots' sensors provide noisy input. A learning autonomous robot, one that can acquire knowledge through;

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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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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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Deep Reinforcement Learning

can be reinforced with positive and negative stimuli. When we see how reinforcement learning teaches a simulated robot to walk, we are;

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Robot Learning Human Skills and Intelligent Control Design

successfully implemented for various robotic tasks. Among these methods, learning from demonstrations (LfD) enables robots to effectively and;

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AI based Robot Safe Learning and Control

neural network, which is an important theoretical branch of deep reinforcement learning. In order to enhance the safety performance of robot;

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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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Deep Reinforcement Learning Hands-On

New edition of the bestselling guide to deep reinforcement learning and how it's used to solve complex real-world problems. Revised and;

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Learning Control

, reinforcement learning control, impedance control, and deep reinforcement control. Each chapter includes case studies and real-world applications;

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Platform Maths

detailed coverage of the key skills and provides a clear structure, small learning steps and strong reinforcement of 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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Learning for Adaptive and Reactive Robot Control

.This book presents a wealth of machine learning techniques to make the control of robots more flexible and safe when;

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Generic Multi-Agent Reinforcement Learning Approach for Flexible Job-Shop Scheduling

job-shop scheduling system for flexible and re-configurable manufacturing systems. Reinforcement Learning approaches are therefore;

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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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Intelligent Robotics and Applications

-machine interface; robot manipulation skills learning; micro_nano materials, devices, and systems for biomedical applications; actuating, sensing;

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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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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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Times Tables Workbook 2

for extra practice and reinforcement of topics covered at school. Age range 5-7. Collins Easy Learning Workbooks help children develop their;

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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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