An application of Markov Decision Programming to ecologico-cybernetics—A decision method applied to the antifrost of winter wheat

Modern ecologico-cybernetic principle is of importance to decreasing damages in relation to agricultural productions. As an illustration of this, the authors studied some of the questions about the optimal policy of choosing actions for the antifrost measures of winter wheat by means of the finite-stage model of Markov Decision Programming (MDP). The related data came from the investigation results of the investigated region in the northeastern part of Henan, China. First, the authors give the states, ecologico-cybernetic action measures, transition probabilities and reward values in relation to these antifrost action measures of winter wheat crop. Second, the authors describe the principles and computational procedures of the ecologico-cybernetic decision-makings based on the finite-stage model of MDP. Third, a simple table applicable to the decision-making practice is given. Finally, we evaluate the results of this study, point out their shortcomings and suggest that this method is applicable to the other fields in relation to decreasing damage ecologico-cybernetics.