Optimized Test Scenario Identification Method based on Refined Warshall's Dynamic Programming for Validating Reinforcement Learning Model.

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Title: Optimized Test Scenario Identification Method based on Refined Warshall's Dynamic Programming for Validating Reinforcement Learning Model.
Authors: Kim, Janghwan1, lentoconstante@hongik.ac.kr, Chul Kim, R. Young1, bob@hongik.ac.kr
Source: KSII Transactions on Internet & Information Systems; Apr2026, Vol. 20 Issue 4, p2224-2241, 18p
Database: Applied Science & Technology Source
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DbLabel: Applied Science & Technology Source
An: 193507006
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  Data: Optimized Test Scenario Identification Method based on Refined Warshall's Dynamic Programming for Validating Reinforcement Learning Model.
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  Data: <searchLink fieldCode="AU" term="%22Kim%2C+Janghwan%22">Kim, Janghwan</searchLink><relatesTo>1</relatesTo>, <i>lentoconstante@hongik.ac.kr</i><br /><searchLink fieldCode="AU" term="%22Chul+Kim%2C+R%2E+Young%22">Chul Kim, R. Young</searchLink><relatesTo>1</relatesTo>, <i>bob@hongik.ac.kr</i>
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      – Type: doi
        Value: 10.3837/tiis.2026.04.030
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      – Code: eng
        Text: English
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        PageCount: 18
        StartPage: 2224
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      – TitleFull: Optimized Test Scenario Identification Method based on Refined Warshall's Dynamic Programming for Validating Reinforcement Learning Model.
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              Text: Apr2026
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              Y: 2026
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