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An introduction to deep reinforcement learning / Vinod K. Mishra.

By: Material type: TextPublication details: Boca Raton: CRC Press, 2026.Edition: First editionDescription: vi, 195 pISBN:
  • 9781032659794
  • 9781032651439
  • 9781032659794
Subject(s): DDC classification:
  • 006.31 23/eng/20251215 MIS
Other classification:
Summary: "The current era of artificial intelligence and machine learning (AIML) tools has transformed the workings of vast swaths of our private, working, and social lives beyond recognition. It has been found that they can solve many problems in better and faster ways compared to humans. AIML tools allow machines and related systems to reason and infer almost like humans, and this has deep intellectual and philosophical ramifications as well. The areas of machine learning are broadly classified into supervised, unsupervised, and deep reinforcement learning (DRL). The last one comes closest to how humans reason, and various innovations in this area have many useful applications. This book covers most of the areas of DRL with a special focus on its mathematical and algorithmic foundations. Undergraduate and early graduate students should find it to be a good guide to the fast-developing areas of DRL and its myriad applications. Hopefully, it will spur them to dive deep and understand the coming revolution in every aspect of society based on these ideas"-- Provided by publisher.
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Holdings
Item type Current library Home library Collection Call number Status Barcode
Book Dept. of Futures Studies Processing Center Dept. of Futures Studies Non-fiction 006.31 MIS (Browse shelf(Opens below)) Available DFS4678

Includes bibliographical references and index.

"The current era of artificial intelligence and machine learning (AIML) tools has transformed the workings of vast swaths of our private, working, and social lives beyond recognition. It has been found that they can solve many problems in better and faster ways compared to humans. AIML tools allow machines and related systems to reason and infer almost like humans, and this has deep intellectual and philosophical ramifications as well. The areas of machine learning are broadly classified into supervised, unsupervised, and deep reinforcement learning (DRL). The last one comes closest to how humans reason, and various innovations in this area have many useful applications. This book covers most of the areas of DRL with a special focus on its mathematical and algorithmic foundations. Undergraduate and early graduate students should find it to be a good guide to the fast-developing areas of DRL and its myriad applications. Hopefully, it will spur them to dive deep and understand the coming revolution in every aspect of society based on these ideas"-- Provided by publisher.

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