Adversarial Decision-Making for Moving Target Defense: A Multi-Agent Markov Game and Reinforcement Learning Approach

Reinforcement learning has shown a great ability and has defeated human beings in the field of real-time strategy games. In recent years, reinforcement learning has been used in cyberspace to carry out automated and intelligent attacks. Traditional defense methods are not enough to deal with this pr...

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Detalles Bibliográficos
Autores principales: Yao, Qian, Wang, Yongjie, Xiong, Xinli, Wang, Peng, Li, Yang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10137508/
https://www.ncbi.nlm.nih.gov/pubmed/37190393
http://dx.doi.org/10.3390/e25040605

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10137508/
https://www.ncbi.nlm.nih.gov/pubmed/37190393
http://dx.doi.org/10.3390/e25040605

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