@inproceedings{87f41fc896ba4e73b44a1960be982c27,
title = "System Vulnerability Oriented to Strategies",
abstract = "System vulnerability has received more and more attention. However, traditional methods of vulnerability are difficult to apply to multi-agent systems with complex game relations with constraints, and research on competition and cooperative relationships rarely considers its system background and constraints. This paper summarizes the existing research and uses reinforcement learning technology to abstract the complex relationship with constraints into a multi-agent model. Through simulation analysis, the impact of three different strategies on system vulnerability is obtained, and provides solutions to improve the vulnerability of the system.",
keywords = "Game Theory, Multi-Agent System, Reinforcement Learning, Strategic Analysis, System Vulnerability, component",
author = "Yu Xin and Xiaohong Bao",
note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 7th International Conference on Dependable Systems and Their Applications, DSA 2020 ; Conference date: 28-11-2020 Through 29-11-2020",
year = "2020",
month = nov,
doi = "10.1109/DSA51864.2020.00085",
language = "英语",
series = "Proceedings - 2020 7th International Conference on Dependable Systems and Their Applications, DSA 2020",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "493--499",
booktitle = "Proceedings - 2020 7th International Conference on Dependable Systems and Their Applications, DSA 2020",
address = "美国",
}