{"product_id":"reward-and-learn-practical-reinforcement-learning-for-autonomous-agents-games-and-robot-control-9798257909924","title":"Reward and Learn: Practical Reinforcement Learning for Autonomous Agents, Games, and Robot Control","description":"\u003cp\u003e • Author(s): Richard Boozman\u003cbr\u003e • Publisher: Independently Published\u003cbr\u003e • Publisher Imprint: Independently Published\u003cbr\u003e • BISAC: Artificial Intelligence - Generative AI\u003c\/p\u003e\u003cp\u003e\u003cb\u003eTrain intelligent systems that learn from interaction, adapt to environments, and improve over time\u003c\/b\u003e\u003c\/p\u003e\u003cp\u003eSome systems are programmed.\u003cbr\u003eOthers learn.\u003c\/p\u003e\u003cp\u003eReinforcement learning enables machines to make decisions, learn from experience, and improve through feedback. It powers everything from game playing AI to robotics and autonomous control.\u003c\/p\u003e\u003cp\u003e\"Reward and Learn\" is a practical, hands on guide to building reinforcement learning systems using Python and modern ML frameworks such as PyTorch.\u003c\/p\u003e\u003cp\u003eThis book focuses on real implementation, helping you move from theory to working intelligent agents.\u003c\/p\u003e\u003cbr\u003eWhy reinforcement learning matters\u003cp\u003eReinforcement learning is the foundation of decision making AI.\u003c\/p\u003e\u003cp\u003e\u003cb\u003eWith the right approach, you can build systems that: \u003c\/b\u003e\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003elearn optimal actions through trial and error\u003c\/li\u003e\n\u003cli\u003eadapt to changing environments\u003c\/li\u003e\n\u003cli\u003emaximize long term rewards\u003c\/li\u003e\n\u003cli\u003econtrol complex systems\u003c\/li\u003e\n\u003cli\u003edevelop intelligent strategies\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eThis book shows you how to build these systems step by step.\u003c\/p\u003e\u003cbr\u003e\u003cb\u003eWhat you will learn\u003c\/b\u003e\u003cul\u003e\n\u003cli\u003efundamentals of reinforcement learning\u003c\/li\u003e\n\u003cli\u003eagents, environments, states, and rewards\u003c\/li\u003e\n\u003cli\u003evalue based and policy based methods\u003c\/li\u003e\n\u003cli\u003eQ learning and deep Q networks\u003c\/li\u003e\n\u003cli\u003epolicy gradients and actor critic methods\u003c\/li\u003e\n\u003cli\u003etraining agents in simulated environments\u003c\/li\u003e\n\u003cli\u003ereward design and optimization\u003c\/li\u003e\n\u003cli\u003eexploration vs exploitation strategies\u003c\/li\u003e\n\u003cli\u003escaling reinforcement learning systems\u003c\/li\u003e\n\u003cli\u003eapplying RL to robotics and control\u003c\/li\u003e\n\u003c\/ul\u003e\u003cbr\u003eFrom algorithms to intelligent agents\u003cp\u003e\u003cb\u003eThroughout the book, you will learn how to: \u003c\/b\u003e\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003ebuild RL agents from scratch\u003c\/li\u003e\n\u003cli\u003etrain agents to solve tasks and games\u003c\/li\u003e\n\u003cli\u003edesign effective reward systems\u003c\/li\u003e\n\u003cli\u003eapply deep learning to RL problems\u003c\/li\u003e\n\u003cli\u003edebug and improve agent performance\u003c\/li\u003e\n\u003cli\u003edeploy RL systems in real applications\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eEach chapter is designed to produce working results.\u003c\/p\u003e\u003cbr\u003e\u003cb\u003ePractical applications\u003c\/b\u003e\u003cul\u003e\n\u003cli\u003egame playing AI agents\u003c\/li\u003e\n\u003cli\u003eautonomous robotics control\u003c\/li\u003e\n\u003cli\u003erecommendation systems\u003c\/li\u003e\n\u003cli\u003eresource optimization systems\u003c\/li\u003e\n\u003cli\u003esimulation based learning\u003c\/li\u003e\n\u003cli\u003eintelligent decision making systems\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eThese examples reflect real world applications of RL.\u003c\/p\u003e\u003cbr\u003e\u003cb\u003eWho this book is for\u003c\/b\u003e\u003cul\u003e\n\u003cli\u003emachine learning engineers\u003c\/li\u003e\n\u003cli\u003eAI developers\u003c\/li\u003e\n\u003cli\u003edata scientists\u003c\/li\u003e\n\u003cli\u003erobotics engineers\u003c\/li\u003e\n\u003cli\u003edevelopers interested in intelligent systems\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003e\u003ci\u003e\u003cb\u003eIf you want to build systems that learn from experience and adapt intelligently, this book provides the roadmap.\u003c\/b\u003e\u003c\/i\u003e\u003c\/p\u003e\u003cp\u003e\u003ci\u003e\u003cb\u003eLearn from feedback.\u003cbr\u003eOptimize decisions.\u003cbr\u003eBuild intelligent agents.\u003c\/b\u003e\u003c\/i\u003e\u003c\/p\u003e","brand":"Independently Published","offers":[{"title":"Paperback","offer_id":47882754195607,"sku":"9798257909924","price":2093.0,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0666\/3471\/1191\/files\/9798257909924.webp?v=1781096814","url":"https:\/\/atlanticbooks.com\/products\/reward-and-learn-practical-reinforcement-learning-for-autonomous-agents-games-and-robot-control-9798257909924","provider":"Atlantic Books","version":"1.0","type":"link"}