Hu Xiaoqing. Analysis of Innovation Degree of Agricultural Science and Technology Service System Based on Markov Decision Process. Dynamic Systems and Applications 29 (2020) No. 5, 2010 – 2019

https://doi.org/10.46719/dsa202029535

ABSTRACT.
Therefore, achieving greater compatibility between these aspects of the agricultural innovation system based on greater agricultural productivity growth and poverty reduction measures. The agricultural science and technology policy analysis presented here goes beyond the current boundaries of agricultural economy into disciplines such as public finance, public management, politics, history, sociology, and psychology. This section presents an innovative and experimental model that takes into account the political economy of public investment in agricultural science and technology and the general policy that organizational and management addresses innovation activities. The economics of science and industrial innovation has embraced some disciplines and has benefited from having done so because of the industrial policy in the developed world. The agricultural Markov Decision Process (MDP) analysis presented here goes beyond the current boundaries of agricultural economy into disciplines such as public finance, public management, political science, history, sociology, and psychology. The economics of science and industrial innovation has embraced some disciplines and has benefited from having done so because of the industrial policy in the developed world. The basic level of agricultural development policy and the recommendations of the long-distance agricultural Markov decision-making process have the same high rate of return for agricultural economics as done in agricultural science and innovation.

Keywords: Markov Decision Process, Agricultural Science and Technology, Agricultural Economics.