Presents an SHT-driven framework for adversarial decision-making in partially observable multi-agent systems formulated as a partially observable Stackelberg game, with semi-explicit optimal controls for the blue team in LQ settings and iterative/ML methods for the red team.
Pham, Continuous-Time Stochastic Control and Optimization with Financial Applications, Springer Science & Business Media, 2009
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Adversarial Decision-Making in Partially Observable Multi-Agent Systems: A Sequential Hypothesis Testing Approach
Presents an SHT-driven framework for adversarial decision-making in partially observable multi-agent systems formulated as a partially observable Stackelberg game, with semi-explicit optimal controls for the blue team in LQ settings and iterative/ML methods for the red team.