随机多风险SIR大流行模型的路径积分控制。

IF 1.3 4区 生物学 Q3 BIOLOGY
Paramahansa Pramanik
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引用次数: 3

摘要

本文采用费曼型路径积分控制方法,递归构建了受疲劳动力学影响的健康目标函数,即具有风险群体贝叶斯意见动态的前瞻性随机多风险易感感染恢复(SIR)模型。我的主要兴趣在于解决政策制定者的社会成本最小化问题,这取决于一些确定性的权重。我从威克旋转Schrödinger-type方程中获得了最佳锁定强度,该方程类似于哈密顿-雅可比-贝尔曼(HJB)方程。我的公式基于路径积分控制和动态规划工具,便于分析并允许应用算法获得流行病控制模型的数值解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Path integral control of a stochastic multi-risk SIR pandemic model.

Path integral control of a stochastic multi-risk SIR pandemic model.

In this paper a Feynman-type path integral control approach is used for a recursive formulation of a health objective function subject to a fatigue dynamics, a forward-looking stochastic multi-risk susceptible-infective-recovered (SIR) model with risk-group's Bayesian opinion dynamics toward vaccination against COVID-19. My main interest lies in solving a minimization of a policy-maker's social cost which depends on some deterministic weight. I obtain an optimal lock-down intensity from a Wick-rotated Schrödinger-type equation which is analogous to a Hamiltonian-Jacobi-Bellman (HJB) equation. My formulation is based on path integral control and dynamic programming tools facilitates the analysis and permits the application of algorithm to obtain numerical solution for pandemic control model.

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来源期刊
Theory in Biosciences
Theory in Biosciences 生物-生物学
CiteScore
2.70
自引率
9.10%
发文量
21
审稿时长
3 months
期刊介绍: Theory in Biosciences focuses on new concepts in theoretical biology. It also includes analytical and modelling approaches as well as philosophical and historical issues. Central topics are: Artificial Life; Bioinformatics with a focus on novel methods, phenomena, and interpretations; Bioinspired Modeling; Complexity, Robustness, and Resilience; Embodied Cognition; Evolutionary Biology; Evo-Devo; Game Theoretic Modeling; Genetics; History of Biology; Language Evolution; Mathematical Biology; Origin of Life; Philosophy of Biology; Population Biology; Systems Biology; Theoretical Ecology; Theoretical Molecular Biology; Theoretical Neuroscience & Cognition.
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