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At present, the mortgage loan of farmland contractual management right is in the pilot and exploration stage. In this overall environment, how to formulate an appropriate pricing model according to the particularity of farmland property right and the actual situation is the theoretical support to be solved. On the basis of theoretical analysis, model construction and analysis of existing problems, this paper establishes a binary tree pricing method of farmland management right mortgage based on machine learning and complex network algorithm. This paper analyzes the basic theory of rural land management right mortgage pricing and constructs the pricing model. Based on the Markov decision process model of dynamic pricing problem, this paper proposes the solution algorithm and proposes the dynamic pricing solution for this paper from two aspects of value function and strategy gradient reinforcement learning algorithm. This paper analyzes the basic principle of A3C algorithm and expounds the algorithm design and neural network architecture for the specific dynamic pricing problem in this paper. The dynamic pricing method of rural land mortgage based on deep reinforcement learning designed in this paper can well predict the real price of rural land management right mortgage pricing and effectively optimize the mortgage loan environment of rural contracted land management right, which is the innovation of financial system in the current new rural construction. [ABSTRACT FROM AUTHOR]