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Reinforcement learning [2nd ed.] : an Introduction

By: Sutton, Richard.
Contributor(s): Barto, Andrew G.
Series: Adaptive computation and machine learning. / edited by Francis Bach.Publisher: Cambridge MIT Press 2020Edition: 2nd ed.Description: xxii, 526p.ISBN: 9780262039246.Subject(s): Reinforcement learningDDC classification: 006.3 | Su87r2 Summary: "Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives while interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the field's key ideas and algorithms.
List(s) this item appears in: New arrivals April 15 to May 19, 2024
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006.3 Su87r2 cop.1 Reinforcement learning [2nd ed.] 006.3 Su87r2 cop.10 Reinforcement learning [2nd ed.] 006.3 Su87r2 cop.2 Reinforcement learning [2nd ed.] 006.3 Su87r2 cop.3 Reinforcement learning [2nd ed.] 006.3 Su87r2 cop.4 Reinforcement learning [2nd ed.] 006.3 Su87r2 cop.5 Reinforcement learning [2nd ed.] 006.3 Su87r2 cop.6 Reinforcement learning [2nd ed.]

"Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives while interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the field's key ideas and algorithms.

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