Falsification of Cyber-Physical Systems Using Deep Reinforcement Learning

Author:

Akazaki Takumi,Liu Shuang,Yamagata Yoriyuki,Duan Yihai,Hao Jianye

Publisher

Springer International Publishing

Cited by 34 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Scenario-Based Flexible Modeling and Scalable Falsification for Reconfigurable CPSs;Lecture Notes in Computer Science;2024

2. Exploring the role of simulator fidelity in the safety validation of learning‐enabled autonomous systems;AI Magazine;2023-11-27

3. Robust Testing for Cyber-Physical Systems using Reinforcement Learning;Proceedings of the 21st ACM-IEEE International Conference on Formal Methods and Models for System Design;2023-09-21

4. Generative Model-Based Testing on Decision-Making Policies;2023 38th IEEE/ACM International Conference on Automated Software Engineering (ASE);2023-09-11

5. Metamorphic relations via relaxations: an approach to obtain oracles for action-policy testing;Proceedings of the 31st ACM SIGSOFT International Symposium on Software Testing and Analysis;2022-07-18

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