£174.98

About as cheap as it gets — within 5% of the all-time low it hit 1 month ago.

£175 today · all-time low £173 (Sep 2026) · usually £175

Springer Reinforcement Learning - Springer Series Vol. 173

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£176.12 £172.38 £173.20 £174.01 £174.83 £175.64 £176.46 28 July 2026 18 August 2026 08 September 2026 29 September 2026 21 October 2026
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16 days 56 days · current 14 days 0 14 28 42 56 £173 £175 £176 Days at Price

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Most common price: £175 (56 days, 65.1%)

Price range: £173 - £176

Price levels: 3 different prices over 86 days

Description

Reinforcement Learning explores the foundational principles of learning mappings from situations to actions to maximise scalar reward signals. This comprehensive volume from Springer's International Series in Engineering and Computer Science (Volume 173) addresses the core mechanisms of trial-and-error search and delayed reward mechanisms that distinguish reinforcement learning from traditional machine learning approaches. The text examines how learners discover optimal actions through experimentation rather than explicit instruction, and how immediate actions shape both present rewards and future states. Essential for understanding autonomous decision-making systems, this book provides theoretical foundations and practical insights into designing agents that learn through interaction with their environments, making it invaluable for researchers, practitioners, and students in artificial intelligence and machine learning.

Key Features

Springer's Volume 173 in the International Series covers foundational reinforcement learning theory and applications.

Examines trial-and-error search mechanisms and delayed reward characteristics central to autonomous learning systems.

Addresses how actions affect immediate rewards and shape subsequent states for optimal long-term decision-making.

Provides essential theory for researchers and practitioners developing intelligent agents that learn through environmental interaction.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
31 May 1992
Listed Since
15 February 2007

Barcode

No barcode data available

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