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Reinforcement Learning: An Introduction 2Nd Edition Hardcover
₹2,999
₹5,999
50% OffFinal Price inclusive of all taxes
size
18.4 x 3.8 x 23.6 cm
Product Information
Brand Name
Books Kingdom
Ideal For
General Readers, Fiction Lovers, Mythology & Historical Fiction Readers, Indian Mythology Enthusiasts, Young Adults (YA) & Adults, College Students, Competitive Exam Aspirants (General Reading / Culture), Gift Purpose (Books Gift Set), Spiritual & Philosophy Interest Readers, Library / Book Collection Buyers
Material
Hardcover
Country Of Origin
India
Pack Of
1
About Author
Richard S. Sutton Is Professor Of Computing Science And Aitf Chair In Reinforcement Learning And Artificial Intelligence At The University Of Alberta, And Also Distinguished Research Scientist At Deepmind.
Author Name
Richard S. Sutton
Genre
Programming & Software Development
No Of Pages
552
Publisher
Mit Press
Product Description
- Premium Quality: Reinforcement Learning: An Introduction is a clear and authoritative account of one of the most active research areas in artificial intelligence, written by leading experts Richard Sutton and Andrew Barto.
- Product Design: This second edition has been significantly expanded and updated, presenting new topics and updating coverage of other topics to reflect the latest developments in the field.
- User Experience: Reinforcement learning is a computational approach to learning whereby an agent tries to maximise the total amount of reward it receives while interacting with a complex, uncertain environment - and Sutton and Barto provide a clear and simple account of the field's key ideas and algorithms.
- Versatile Occasion: Suitable for students, researchers, and practitioners across artificial intelligence, machine learning, and computing science who seek a rigorous yet accessible introduction to reinforcement learning.
- Lifestyle Essential: A definitive and widely respected textbook in the field of AI and machine learning, this hardcover second edition is an indispensable resource for anyone serious about understanding reinforcement learning.
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