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基于DQN的企业创业创新自主体模拟

Agent-Based Simulation of Enterprise Entrepreneurship and Innovation Based on DQN
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摘要 基于自主体的计算经济学(ACE),利用自主体模型构建了一个以企业行为为基础的经济系统模型,试图解决企业创新与创业结合的动力学问题和政策问题。在文章构建的企业创业创新经济系统中,作为企业自主体行动的自主体行为算法是采用人工智能的DQN算法进行自适应模拟的。模拟得到结论:相比于没有自适应行为的企业自主体,具有自适应行为的企业自主体能够更好地通过对环境和自身状态的评估,进行正确的企业决策。 Based on ACE (Agent-based Computational Economics),this paper uses an agent-based model to build an economic system model based on enterprise behavior,and tries to solve the dynamic problem and policy problem of combining enterprise innovation with entrepreneurship. In the economic system of enterprise entrepreneurship and innovation constructed in this paper,the agent behavior algorithm,which acts as the enterprise agent,adopts the artificial intelligence DQN algorithm for self-adaptive simulation. The simulation results show that compared with the enterprise agent without self-adaptive behavior,the enterprise agent with self-adaptive behavior is able to make correct business decisions by evaluating the environment and its own state.
作者 李睿 王铮 LI Rui;WANG Zheng(Key Laboratory of Geographical Information Science,Ministry of State Education of China,East China Normal University,Shanghai 200241,China;Institute of Policy and Management Science,Chinese Academy of Sciences,Beijing 100080,China)
出处 《复杂系统与复杂性科学》 EI CSCD 2019年第1期43-53,共11页 Complex Systems and Complexity Science
基金 国家自然科学基金(D010701)
关键词 DQN 自适应学习 自主体模拟 技术进步 企业决策 DQN self-adaptive learning agent-based simulation technological advance business decisions
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  • 1王铮,吴静,杨念.多自主体在地理学中应用的回顾与展望[J].复杂系统与复杂性科学,2005,2(3):52-60. 被引量:21
  • 2WANG Zheng (Institute of Policy and Management, Chinese Academy of Sciences, Beijing 100080, China).Spatial interaction: a statistical mechanism model[J].Journal of Geographical Sciences,2000,10(3):87-92. 被引量:5
  • 3薛领,诸叶平,雪燕,王滔.基于Agent的农业经济智能决策支持系统研究[J].农业系统科学与综合研究,2004,20(3):172-176. 被引量:11
  • 4戴霄晔,刘涛,王铮.面向产业创业创新政策模拟的ABS系统开发[J].复杂系统与复杂性科学,2007,4(2):62-70. 被引量:8
  • 5[1]Lempert R.Agent-based modeling as organizational public policy simulators[J].Proceedings of the National Academy of Sciences of the United States of America,2002,99:7 195-7 196.
  • 6[2]Klos T,Nooteboom B.Agent-based computational transaction cost economics[J].Journal of Economic Dynamics & Control,2001,25:503-526.
  • 7[3]Carpenter J.Evolutionary models of bargaining:comparing agent-based computational and analytical approaches to understanding convention evolution[J].Computational Economics,2002,19:25-49.
  • 8[4]Tesfatsion L.Introduction to the special issue on agent-based computational economics[J].Journal of Economic Dynamics & Control,2001,25:281-293.
  • 9[5]Meyer D,Karatzoglou A,Leisch F,et al.A simulation framework for heterogeneous agents[J].Computational Economics,2003,22:285-301.
  • 10[6]Chaturvedi A,Mehta S,Dolk D,et al.Agent-based simulation for computational experimentation:developing an artificial labor market[J].European Journal of Operational Research,2005,166:694-716.

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