The Mathematics of Infectious Diseases
SIAM Review
The Complexity of Decentralized Control of Markov Decision Processes
Mathematics of Operations Research
Equivalence notions and model minimization in Markov decision processes
Artificial Intelligence - special issue on planning with uncertainty and incomplete information
Sequential optimality and coordination in multiagent systems
IJCAI'99 Proceedings of the 16th international joint conference on Artifical intelligence - Volume 1
Planning and acting in partially observable stochastic domains
Artificial Intelligence
Hi-index | 0.00 |
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 decision-maker 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.