Learning attack-defense response in continuous-time discrete-states Stackelberg Security Markov games
Author:
Affiliation:
1. Escuela Superior de Física y Matemáticas, Instituto Politécnico Nacional, Ciudad de Mexico, Mexico
2. School of Physics and Mathematics, National Polytechnic Institute, Mexico City, Mexico
Publisher
Informa UK Limited
Subject
Artificial Intelligence,Theoretical Computer Science,Software
Link
https://www.tandfonline.com/doi/pdf/10.1080/0952813X.2022.2135615
Reference36 articles.
1. A Stackelberg security Markov game based on partial information for strategic decision making against unexpected attacks
2. Repeated Stackelberg security games: Learning with incomplete state information
3. Controller exploitation-exploration reinforcement learning architecture for computing near-optimal policies
4. Commitment Without Regrets
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1. Continuous-Time Markov Chains;Optimization and Games for Controllable Markov Chains;2023-12-14
2. Fault‐tolerant secure H∞$$ H\infty $$ synchronization for complex networks with semi‐Markov jump topology;International Journal of Adaptive Control and Signal Processing;2023-09-14
3. Computing fortification games in a tri-level Stackelberg Markov chains approach;Engineering Applications of Artificial Intelligence;2023-05
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