Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Ryeonggu Kwon"'
Publikováno v:
IEEE Access, Vol 12, Pp 18957-18971 (2024)
Reinforcement learning (RL) is rapidly used in safety-centric applications. However, many studies focus on generating optimal policy that achieves maximum rewards. While maximum rewards are beneficial, safety constraints and non-functional requiremen
Externí odkaz:
https://doaj.org/article/668cbde48aa344a19a7bc3d23c76e92d
Publikováno v:
Applied Sciences, Vol 14, Iss 7, p 2812 (2024)
In modern software development, OSS (Open Source Software) has become a crucial element. However, if OSS have few contributors and are lacking in maintenance activities, such as bug fixes, are used, it can lead to significant costs and resource alloc
Externí odkaz:
https://doaj.org/article/150cc8188db041d4a47e50239fbb612b
Publikováno v:
Applied Sciences, Vol 14, Iss 7, p 2916 (2024)
Experience-based methods like reinforcement learning (RL) are often deemed less suitable for the safety field due to concerns about potential safety issues. To bridge this gap, we introduce STPA-RL, a methodology that integrates RL with System-Theore
Externí odkaz:
https://doaj.org/article/c82ace683f644ea2847a6376e4167e06
Publikováno v:
Applied Sciences, Vol 14, Iss 3, p 1260 (2024)
GitHub serves as a platform for collaborative software development, where contributors engage, evolve projects, and shape the community. This study presents a novel approach to analyzing GitHub activity that departs from traditional methods. Using Di
Externí odkaz:
https://doaj.org/article/df501819b4264fd7b968816902333f87
Autor:
Ryeonggu Kwon, Gihwon Kwon
Publikováno v:
Scientific Journal of Gdynia Maritime University, Iss 125 (2023)
As technology advances, hardware-centric systems are rapidly moving towards software-centric ones, and their complexity is rapidly increasing. In particular, systems directly related to safety require thorough verification. Model checking exhaustivel
Externí odkaz:
https://doaj.org/article/981bb5175b4e49c0940ac251872c00d6
Autor:
Ryeonggu Kwon, Gihwon Kwon
Publikováno v:
Systems, Vol 11, Iss 11, p 535 (2023)
In the context of reinforcement learning (RL), ensuring both safety and performance is crucial, especially in real-world scenarios where mistakes can lead to severe consequences. This study aims to address this challenge by integrating temporal logic
Externí odkaz:
https://doaj.org/article/4a1c31913096407e9b0d93cb9aa50ba6
Publikováno v:
The Journal of Korean Institute of Information Technology. 20:167-174
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7e2d498a39fb1256ad5582b51d5a3820
https://doi.org/10.14801/jkiit.2022.20.12.167
https://doi.org/10.14801/jkiit.2022.20.12.167