Reinforcement learning for cyber operations : applications of artificial intelligence for penetration testing /
"Reinforcement learning (RL) is an area of machine learning concerned with how intelligent agents ought to take actions in an environment in order to maximize the notion of cumulative reward. Reinforcement learning is one of three basic machine learning paradigms, alongside supervised learning...
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| Format: | eBook |
| Language: | English |
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Hoboken, New Jersey :
Wiley,
[2025]
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| Online Access: | Connect to the full text of this electronic book |
| Summary: | "Reinforcement learning (RL) is an area of machine learning concerned with how intelligent agents ought to take actions in an environment in order to maximize the notion of cumulative reward. Reinforcement learning is one of three basic machine learning paradigms, alongside supervised learning and unsupervised learning. Reinforcement learning differs from supervised learning in not needing labelled input/output pairs to be presented, and in not needing sub-optimal actions to be explicitly corrected. Instead the focus is on finding a balance between exploration (of uncharted territory) and exploitation (of current knowledge)."-- |
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| Physical Description: | 1 online resource (xxx, 256 pages) : illustrations (some color) |
| Bibliography: | Includes bibliographical references and index. |
| ISBN: | 9781394206476 139420647X 9781394206469 1394206461 9781394206483 1394206488 |