Defense and security planning under resource uncertainty and multi‐period commitments
针对国防安全中下级组织在不确定资源和环境下进行长期规划的问题，提出了一个结合对抗风险分析与马尔可夫决策过程的建模框架，并通过反恐案例验证了其有效性。
Abstract The public sector is characterized by hierarchical and interdependent organizations. For defense and security applications in particular, a higher authority is generally responsible for allocating resources among subordinate organizations. These subordinate organizations conduct long‐term planning based on both uncertain resources and an uncertain operating environment. This article develops a modeling framework and multiple solution methodologies for subordinate organizations to use under such conditions. We extend the adversarial risk analysis approach to a stochastic game via a decomposition into a Markov decision process. This allows the subordinate organization to encode its beliefs in a Bayesian manner such that long‐term policies can be built to maximize its expected utility. The modeling framework we develop is illustrated in a realistic counter‐terrorism use case, and the efficacy of our solutions are evaluated via comparisons to alternatively constructed policies.