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RADAR: A FRAMEWORK FOR DEVELOPING ADVERSARIALLY ROBUST CYBER DEFENSE AI AGENTS WITH DEEP REINFORCEMENT LEARNING.

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Title: RADAR: A FRAMEWORK FOR DEVELOPING ADVERSARIALLY ROBUST CYBER DEFENSE AI AGENTS WITH DEEP REINFORCEMENT LEARNING.
Authors: Ebrahimi, Reza1 ebrahimim@usf.edu, Chai, Yidong2 weifeng.li@uga.edu, Li, Weifeng3 pachecoj@cs.arizona.edu, Pacheco, Jason4 hsinchun@arizona.edu, Chen, Hsinchun5
Source: MIS Quarterly. Dec2025, Vol. 49 Issue 4, p1385-1416. 32p. 11 Color Photographs, 2 Diagrams, 10 Charts.
Database: Business Source Ultimate
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  Data: RADAR: A FRAMEWORK FOR DEVELOPING ADVERSARIALLY ROBUST CYBER DEFENSE AI AGENTS WITH DEEP REINFORCEMENT LEARNING.
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  Data: <searchLink fieldCode="JN" term="%22MIS+Quarterly%22">MIS Quarterly</searchLink>. Dec2025, Vol. 49 Issue 4, p1385-1416. 32p. 11 Color Photographs, 2 Diagrams, 10 Charts.
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=bsu&AN=189744266
RecordInfo BibRecord:
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      – Type: doi
        Value: 10.25300/misq/2024/17339
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      – Code: eng
        Text: English
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        PageCount: 32
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      – TitleFull: RADAR: A FRAMEWORK FOR DEVELOPING ADVERSARIALLY ROBUST CYBER DEFENSE AI AGENTS WITH DEEP REINFORCEMENT LEARNING.
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            NameFull: Ebrahimi, Reza
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            NameFull: Chai, Yidong
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            NameFull: Li, Weifeng
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            NameFull: Pacheco, Jason
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            NameFull: Chen, Hsinchun
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            – D: 01
              M: 12
              Text: Dec2025
              Type: published
              Y: 2025
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              Value: 49
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