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10958606
Reinforcement Learning, second edition: An Introduction (Adaptive Computation and Machine Learning series)
87% of respondents would recommend this to a friend
Item #:
10958606
BHD 38
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The significantly expanded and updated new edition of a widely used text on reinforcement learning
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What Stands Out
Comprehensive Content
This second edition offers an in-depth exploration of reinforcement learning, combining theoretical insights with practical applications, making it an essential resource for students and professionals in the field.
Updated Research
Includes the latest advancements in reinforcement learning techniques and methodologies, ensuring readers are equipped with current trends and best practices necessary for effective implementation in real-world scenarios.
Adaptive Learning
Designed for varied audiences, from beginners to advanced practitioners, this book presents concepts in an accessible manner, promoting understanding and enabling readers to apply reinforcement learning principles across diverse domains.
Product Details
| Package Weight | 3.0 Pound |
Who Should Buy?
-
Students and Academics
Ideal for those studying advanced topics in machine learning and seeking a solid foundation in reinforcement learning concepts.
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Data Scientists
Useful for data scientists looking to expand their skill set with practical reinforcement learning applications and techniques.
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Researchers
Valuable for researchers interested in the latest developments and theories in reinforcement learning within computational intelligence.
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Beginners
Not suitable for complete beginners as it assumes prior knowledge of machine learning and programming concepts.
Product Description
Reinforcement Learning, second edition: An Introduction (Adaptive Computation and Machine Learning series)
About This Item
Introducing "Reinforcement Learning: An Introduction" - The Ultimate Guide to Understanding and Mastering Reinforcement Learning! Are you fascinated by the concept of machine learning and eager to explore its applications? Look no further! "Reinforcement Learning: An Introduction" is the comprehensive resource you’ve been searching for. As a part of the renowned Adaptive Computation and Machine Learning series, this hardcover book is an essential addition to any enthusiast's library. It provides a detailed and insightful introduction to reinforcement learning, a subfield of machine learning that focuses on decision-making and optimization in dynamic environments. In this illustrated edition, you'll find a wealth of knowledge and practical insights to help you navigate the world of reinforcement learning. Whether you're a beginner or an experienced practitioner, this book is designed to cater to your needs and enhance your understanding of this cutting-edge technology. With its release in November 2018, this hardcover edition ensures a durable and lasting companion for your learning journey.
Its solid construction and impeccable attention to detail make it a valuable collectible that you can reference time and time again. Designed for anyone eager to dive deeper into the world of reinforcement learning, this book covers topics such as value functions, Monte Carlo methods, temporal difference learning, and so much more. The authors provide clear explanations and intuitive examples to aid your understanding, allowing you to grasp complex concepts effortlessly. Harness the power of reinforcement learning and unlock its potential in various industries, including robotics, gaming, finance, and healthcare. Whether you're a student, researcher, or industry professional, this book will equip you with the knowledge and tools needed to bring your ideas to life. Don't miss out on this must-have resource for mastering reinforcement learning.
Order your hardcover copy of "Reinforcement Learning: An Introduction" today and get ready to embark on an exciting journey through the fascinating world of adaptive computation and machine learning!.
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Product Buying Guide
Reinforcement Learning, second edition: An Introduction (Adaptive Computation and Machine Learning series) 2nd Edition is a widely used text on reinforcement learning, offering a clear and simple account of the field's key ideas and algorithms. The significantly expanded and updated new edition presents new topics and updates coverage of other topics. It is an essential resource for those interested in artificial intelligence and computational learning.
Product Specifications
- Reinforcement Learning, second edition: An Introduction (Adaptive Computation and Machine Learning series) 2nd Edition
- 2nd
- Richard S. Sutton, Andrew G. Barto
- Hardcover
- 775 pages
- The MIT Press
- English
- 0262039249
- 978-0262039246
Key Features
- Covers core online learning algorithms with new sections on function approximation, artificial neural networks, and Fourier basis.
- Significantly expanded and updated second edition with new topics and updated coverage of other topics.
- Includes case studies on reinforcement learning's relationships to psychology and neuroscience, as well as discussions on future societal impacts.
Usage Scenarios
- Ideal for students and researchers in the field of artificial intelligence, machine learning, and computational learning.
- Suitable for professionals seeking to deepen their understanding of reinforcement learning algorithms and their practical applications.
Usage Scenarios
- Reinforcement Learning: An Introduction by Richard S. Sutton and Andrew G. Barto (1st Edition)
- Reinforcement Learning and Optimal Control by Dimitri P. Bertsekas
Some User Review
- The second edition offers comprehensive coverage and updated material, making it an invaluable resource for both academics and professionals.
- The case studies and practical examples greatly enhance the understanding of reinforcement learning algorithms and their real-world applications.
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- The price of the product may vary based on the vendor and location. It is advisable to compare prices from different retailers or online platforms to find the best deal.
Buying Considerations
- Conduct thorough research about the content and compare it with other similar books to ensure it aligns with your learning or professional requirements.
- Compare prices and vendor reputation to make an informed purchase decision.
- Consider user reviews and feedback to gauge the practical value and relevance of the book.
Conclusion
Reinforcement Learning, second edition: An Introduction (Adaptive Computation and Machine Learning series) 2nd Edition is an essential and comprehensive resource for those interested in deepening their understanding of reinforcement learning algorithms and their practical applications in the field of artificial intelligence and machine learning.
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Intelligence & Semantics Editorial Review
Reinforcement Learning, second edition: An Introduction is an essential resource for those delving into adaptive computation and machine learning principles. This second edition not only covers fundamental concepts but also emphasizes practical applications and real-world scenarios in reinforcement learning. Weighing 3.0 pounds, this comprehensive book serves as a valuable guide to both students and professionals, providing insights into advanced techniques and strategies within the field. Readers have appreciated the clear explanations and logical structure of the content, making it accessible for newcomers while still being informative for seasoned experts.
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Pros
- Comprehensive overview of reinforcement learning principles
- Clear explanations and logical structure
- Ideal for both students and professionals
- Covers practical applications and real-world scenarios
Cons
- A bit weighty for casual reading
Product Price History
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Features & Benefits
- Reinforcement Learning is a widely used text in the field
- Provides a clear and simple account of the key ideas and algorithms
- Significantly expanded and updated second edition
- Includes new topics and updated coverage of other topics
- Focuses on core online learning algorithms
- Expands into function approximation and off-policy learning
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