REINFORCEMENT LEARNING AN INTRODUCTION

By:

SUTTON S RICHARD

Contributor(s):

BARTO G ANDREW

Material type:

TextLanguage: ENGLISH Publication details: LONDON THE MIT PRESS 2018Edition: SECOND EDITIONDescription: XIX 526PISBN:

978-0-262-19398-6

Subject(s):

DDC classification:

006.31 SUT

Summary: "Reinforcement Learning: An Introduction" by Richard S. Sutton and Andrew G. Barto is a fundamental textbook detailing how an agent learns optimal decisions by interacting with an environment to maximize a reward signal. The book covers core concepts such as agents, environments, policies, reward signals, and value functions, and explores methods like Dynamic Programming, Monte Carlo, and Temporal-Difference learning.

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Holdings
Cover image	Item type	Current library	Home library	Collection	Shelving location	Call number	Materials specified	Vol info	URL	Copy number	Status	Notes	Date due	Barcode	Item holds	Item hold queue priority	Course reserves
	Reference	Central Library, Aditya Institute of Technology and Management GF-04/L	Central Library, Aditya Institute of Technology and Management	Computer Science		006.3 SUT (Browse shelf(Opens below))					Not for Loan	Reinforcement Learning (RL)		53677

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OPTIMIZATION & AUTOMATION

"Reinforcement Learning: An Introduction" by Richard S. Sutton and Andrew G. Barto is a fundamental textbook detailing how an agent learns optimal decisions by interacting with an environment to maximize a reward signal. The book covers core concepts such as agents, environments, policies, reward signals, and value functions, and explores methods like Dynamic Programming, Monte Carlo, and Temporal-Difference learning.

Computer Science

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