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基于强化学习的农田水利设施管理进化博弈分析
引用本文:黄彬彬,刘青,胡振鹏,刘伟兵.基于强化学习的农田水利设施管理进化博弈分析[J].系统工程理论与实践,2013,33(12):3231-3236.
作者姓名:黄彬彬  刘青  胡振鹏  刘伟兵
作者单位:1. 江西省水文水资源与水环境重点实验室, 南昌 330099;2. 南昌大学 管理科学与工程系, 南昌 330023;3. 武汉大学 政治与公共管理学院, 武汉 430072
基金项目:国家自然科学基金(51309129);水利部公益性行业专项经费(201201016);江西省高等学校重点学科建设项目
摘    要:在对农田水利设施进行管理维护时,由于其公共品属性和农民个人理性,会采取搭便车策略,导致参与积极性不高.首先建立了农民参与农田水利管理的一般模型,然后通过适当的激励方式和组织形式,构建了新的管理模式.考虑农民决策的有限理性,并可以通过对周围环境的学习进行策略调整,利用基于Q-学习的进化博弈理论对农民策略的改变和合作行为进行讨论,并通过仿真实验说明了新的管理模式不仅能够提高上、下游农民的收益,而且能够提高博弈中合作策略的出现次数.

关 键 词:农田水利  管理  进化博弈  Q-学习  
收稿时间:2011-11-24

Evolutionary game analysis of irrigation infrastructures management based on reinforcement learning-model
HUANG Bin-bin,LIU Qing,HU Zhen-peng,LIU Wei-bing.Evolutionary game analysis of irrigation infrastructures management based on reinforcement learning-model[J].Systems Engineering —Theory & Practice,2013,33(12):3231-3236.
Authors:HUANG Bin-bin  LIU Qing  HU Zhen-peng  LIU Wei-bing
Institution:1. Jiangxi Province Key Laboratory of Water Resources and Water Environment, Nanchang 330099, China;2. Department of Management Science and Engineering, Nanchang University, Nanchang 330023, China;3. School of Political Sciences and Public Administration, Wuhan University, Wuhan 430072, China
Abstract:The irrigation infrastructures are public goods, farmers will adopt free-riding strategy in the management and maintenance because of the individual rationality, and so there are only few people engage in the activity. The paper first established the normal model of farmers engaged in the activity, then designed a new manage model by appropriate incentives and organization forms. Farmers not only individual rationality but also can change them strategies by study, so the paper discussed the cooperation and strategy change of the farmers by evolutionary game based of Q-learning. At last, the simulation illustrated that the new model not only improved the income of the upstream and downstream farmers, but also can increase the degree of cooperation in the game.
Keywords:irrigation infrastructures  management  evolutionary game  Q-learning  
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