Research And Application Of Game Theory And Reinforcement Learning In New Energy Vehicle Subsidy Strategies

In recent years,game theory and reinforcement learning have become very popular research fields in today’s society.As the most strategic analysis and optimization research method,they can be used in the study of subsidy strategy of China’s new energy automobile industry to solve the problems caused by the government’s subsidy of new energy vehicles.At present,the main approaches for strategy analysis and optimization include game theory and reinforcement learning.However,there are few researches on reinforcement learning in the subsidy strategy of new energy vehicles.In addition,although the game theory in the new energy car subsidy policy has a certain application,but the game theory in the study of the new energy car subsidy strategy there are still many deficiencies,among them,there are two evident,first of all,establish a game model,most of the research situation is single,without considering the diversity of new energy automobile market.Secondly,most of the researches are based on existing methods,and there are few researches on the methods of strategy evaluation and optimization.In response to the above problems,this paper mainly takes the new energy vehicle market as the background,based on game theory and reinforcement learning,to study the evaluation methods and strategy optimization methods of government subsidies in different situations,and use them in China’s new energy vehicle subsidy strategies and other Applied in the strategy optimization problem.Firstly,based on the game theory,this paper studies the evaluation method of government subsidy strategy in the case of "double reciprocity" and "one strong and one weak" by constructing the "double reciprocity" enterprise game process and the "one strong and one weak" enterprise game process.Next,with the new energy automobile market as the background,new energy automobile market penetration model is studied,and put forward the new energy automobile market in the dynamic game model between the government and the new energy automobile enterprise,and through the combination of enterprise dynamic game model and reinforcement learning model,the optimization of government subsidy policy method is studied.Then,using the proposed government subsidy strategy evaluation method and subsidy strategy optimization method,the effectiveness of China’s new energy vehicle subsidy policy and the optimal subsidy strategy in the new energy vehicle industry are studied.Finally,in order to prove the multi-applicability of the strategy optimization method proposed in this paper,the proposed strategy optimization method has been extended and applied.After careful research,this paper has achieved the following results:(1)Proposed the evaluation method of government subsidy strategy in the case of "double reciprocity" and "one strong and one weak".(2)A dynamic game method and an effective and multi-applicable strategy optimization method are proposed.(3)It is proved that China’s Dual-Credit policy not only plays a positive role in promoting the development of the new energy vehicle market,but also plays a positive role in increasing the income of the new energy vehicle enterprises with strong strength.In addition,it also found the specific influence of some parameters in the Dual-Credit policy on the output of new energy vehicles,NEV credits and CAFC credits.(4)Put forward the government’s optimal subsidy strategy for new energy vehicles and charging piles in different scenarios in the future.