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Using Markov Decision Process to define an adaptive strategy to control the spread of an animal disease
Anne-France Viet, Laurent Jeanpierre, Maroua Bouzid, Abdel-Illah Mouaddib

Using Markov Decision Process to define an adaptive strategy to control the spread of an animal disease

Science & Mathematics Published 2012 Verification Pending

Overview & Synopsis

A strategy to control an animal disease within an area is often based on one or more actions systematically implemented. In this paper, we illustrate how to use a Markov Decision Process (MDP) to compute an adaptive strategy depending on the pathogen spread within a group of farmers with only one decisionmaker for the group. The objective at the group level is to decrease the cost of the disease and its control. Status for each farm is assumed to be exactly known each year by the decision-maker. Possible actions each year are Doing nothing or Vaccinating. The computed MDP policy results in a non-systematic vaccination. Although the objective is only based on the total costs, the computed MDP policy reduces the prevalence, that is the amount of infected herds, compared to a systematically Doing nothing strategy

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Document Information

Document Title Using Markov Decision Process to define an adaptive strategy to control the spread of an animal disease
Author / Organization Anne-France Viet, Laurent Jeanpierre, Maroua Bouzid, Abdel-Illah Mouaddib
Subject & Discipline Multidisciplinary Academic Open Research
Categories Science & Mathematics
Publication Year 2012
License / Rights Open Access / Creative Commons
Resource Verification Listed PDF (Verification Pending)
Original Host Website HAL Open Science (hal.science)
File Format application/pdf (Portable Document Format)
Language EN
Catalog ID DOC-226244
Original Source Link Visit Source Page on hal.science »