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Reinforcement learning for cyber operations :applications of Artificial Intelligence for penetration testing /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Reinforcement learning for cyber operations :Abdul Rahman ... [et al.].
Reminder of title:	applications of Artificial Intelligence for penetration testing /
other author:	Rahman, Abdul
Published:	Hoboken, New Jersey :Wiley,c2025.
Description:	xxx, 256 p. :ill. (some col.) ;24 cm
Subject:	Reinforcement learning.
ISBN:	9781394206452 :

Reinforcement learning for cyber operations :applications of Artificial Intelligence for penetration testing /
Reinforcement learning for cyber operations :applications of Artificial Intelligence for penetration testing /Abdul Rahman ... [et al.]. - Hoboken, New Jersey :Wiley,c2025. - xxx, 256 p. :ill. (some col.) ;24 cm

Includes bibliographical references and index.

"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)."--

ISBN: 9781394206452 :NT$3886

LCCN: 2024049767Subjects--Topical Terms:

349131
Reinforcement learning.

LC Class. No.: Q325.6 / .R34 2025

Dewey Class. No.: 006.3/1

Reinforcement learning for cyber operations :applications of Artificial Intelligence for penetration testing /
LDR:01675cam a2200265 a 4500 001 675762
003 OCoLC
005 20250620042141.0
008 250818s2025 njua b 001 0 eng c
010 $a 2024049767
020 $a 9781394206452 : $c NT$3886
020 $a 1394206453
020 $z 9781394206469 (adobe pdf)
020 $z 9781394206476 (epub)
035 $a (OCoLC)1478244497
035 $a on1478244497
040 $a WaSeSS/DLC $b eng $c DLC $d IG# $d OCLCO $d BDX
042 $a pcc
050 0 0 $a Q325.6 $b .R34 2025
082 0 0 $a 006.3/1 $2 23
245 0 0 $a Reinforcement learning for cyber operations : $b applications of Artificial Intelligence for penetration testing / $c Abdul Rahman ... [et al.].
260 $a Hoboken, New Jersey : $b Wiley, $c c2025.
300 $a xxx, 256 p. : $b ill. (some col.) ; $c 24 cm
504 $a Includes bibliographical references and index.
520 $a "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)."-- $c Provided by publisher.
650 0 $a Reinforcement learning. $3 349131
650 0 $a Penetration testing (Computer security) $3 647045
700 1 $a Rahman, Abdul $c (Executive), $e author. $3 989506
776 0 8 $i Online version: $a Rahman, Abdul (Executive). $t Reinforcement learning for cyber operations $d Hoboken, New Jersey : Wiley, [2025] $z 9781394206469 $w (DLC) 2024049768