REINFORCEMENT LEARNING-DRIVEN AUTONOMOUS SYSTEMS FOR SMART ROBOTICS AND INDUSTRIAL AUTOMATION

<jats:p>Reinforcement Learning-Driven Autonomous Systems for Smart Robotics and Industrial Automation explores the principles, algorithms, and applications of reinforcement learning in developing intelligent autonomous systems. The book covers fundamental concepts, mathematical foundations, deep reinforcement learning techniques, multi-agent learning, and adaptive decision-making strategies. It highlights the integration of reinforcement learning with robotics, industrial automation, smart manufacturing, and cyber-physical systems. Real-world applications such as robotic navigation, predictive maintenance, process optimization, and intelligent control are discussed. The book also addresses challenges including safety, scalability, explainability, and real-time deployment, making it a valuable reference for researchers, students, and industry professionals.</jats:p>