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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...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2023
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| Materias: | |
| 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 |