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A Tractable Leader-Follower MDP Model for Animal Disease Management

机译:用于动物疾病管理的可追踪的领导者跟从者MDP模型

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Sustainable animal disease management requires to design and implement control policies at the regional scale. However, for diseases which are not regulated, individual farmers are responsible for the adoption and successful application of control policies at the farm scale. Organizations (groups of farmers, health institutions...) may try to influence farmers' control actions through financial incentives, in order to ensure sustainable (from the health and economical point of views) disease management policies. Economics / Operations Research frameworks have been proposed for modeling the effect of incentives on agents. The Leader-Follower Markov Decision Processes framework is one such framework, that combines Markov Decision Processes (MDP) and stochastic games frameworks. However, since finding equilibrium policies in stochastic games is hard when the number of players is large, LF-MDP problems are intractable. Our contribution, in this article, is to propose a tractable model of the animal disease management problem. The tractable model is obtained through a few simple modeling approximations which are acceptable when the problem is viewed from the organization side. As a result, we design a polynomial-time algorithm for animal disease management, which we evaluate on a case study inspired from the problem of controlling the spread of the Porcine Reproductive and Respiratory Syndrome (PRRS). Content Area : Animal infectious disease management.
机译:可持续的动物疾病管理要求在区域范围内设计和实施控制政策。但是,对于不受管制的疾病,个体农民有责任在农场范围内采用和成功实施控制政策。组织(农民团体,卫生机构...)可能试图通过财政激励措施影响农民的控制行动,以确保制定可持续的(从健康和经济角度出发)疾病管理政策。已经提出了经济学/运筹学框架来对激励对代理商的影响进行建模。领导者跟随者马尔可夫决策过程框架就是这样一种框架,它结合了马尔可夫决策过程(MDP)和随机博弈框架。但是,由于当玩家数量很大时,很难在随机博弈中找到均衡策略,因此LF-MDP问题很棘手。在本文中,我们的贡献是为动物疾病管理问题提出了一个易于处理的模型。易处理的模型是通过一些简单的建模近似获得的,当从组织的角度来看问题时,这些近似是可以接受的。结果,我们设计了一种用于动物疾病管理的多项式时间算法,并根据一个案例研究进行了评估,该案例的灵感来自于控制猪繁殖与呼吸综合征(PRRS)传播的问题。内容领域:动物传染病管理。

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