计算机工程与应用 ›› 2011, Vol. 47 ›› Issue (35): 25-27.

• 博士论坛 • 上一篇    下一篇

网格资源非对称进化博弈分配策略

张小庆1,2,李春林2,张恒喜2,3,钱琼芬2,4   

  1. 1.黄冈师范学院 数学与计算机科学学院,湖北 黄冈 438000
    2.武汉理工大学 计算机科学与技术学院,武汉 430063
    3.徐州空军学院 基础部,江苏 徐州 221000
    4.空军雷达学院 第四部,武汉 430019
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2011-12-11 发布日期:2011-12-11

Asymmetric evolutionary game allocation strategy of grid resource

ZHANG Xiaoqing1,2,LI Chunlin2,ZHANG Hengxi2,3,QIAN Qiongfen2,4   

  1. 1.College of Mathematics and Computer Science,Huanggang Normal University,Huanggang,Hubei 438000,China
    2.School of Computer Science and Technology,Wuhan University of Technology,Wuhan 430063,China
    3.Department of Fundamental,Xuzhou Air Force Academy,Xuzhou,Jiangsu 221000,China
    4.No.4 Department,Air Force Radar Academy,Wuhan 430019,China
  • Received:1900-01-01 Revised:1900-01-01 Online:2011-12-11 Published:2011-12-11

摘要: 针对经济模型的网格系统中资源分配的竞争问题,应用进化博弈论中多种群复制动态博弈模型对有限理性网格用户有差别的出价策略进行了研究,提出了一种非对称进化资源分配博弈模型,该模型将网格用户分为出价偏低的保守种群和出价偏高的激进种群,分析了两种网格种群采取合作与竞争策略的自发进化过程,求解了各自的复制动态方程,并通过实例化的非对称支付矩阵求解了复制动态系统的进化稳定策略。研究表明,只有博弈双方选择对等的行为策略才能促进网格资源的公平分配。

关键词: 网格, 资源分配, 进化博弈, 复制动态, 进化稳定策略

Abstract: Aiming at the heterogeneity of users in grid system based on economic model,the evolutionary game theory of multi-population replicator dynamics is applied to research different bidding strategies of grid users with bounded rationality.The grid users are divided into conservative population with low bidding and radical population with high bidding,and the spontaneous evolutionary process of cooperation and competition strategy in two grid populations is analyzed.Finally,the replicator dynamics equation is solved respectively and evolutionarily stable strategies of replicator dynamics system are obtained through a specific asymmetric payoff matrix.The studies show that only reciprocal behavior strategies selected by two game sides can promote equitable allocation of grid resources.

Key words: grid, resource allocation, evolutionary game, replicator dynamics, evolutionarily stable strategy