期刊文献+

多智能体系统中基于演化博弈的群体状态控制 被引量:3

Control of states based on evolutionary games in multi-agent systems
下载PDF
导出
摘要 在对多智能体系统的研究中,如何通过施加最少的控制来使某种策略在群体中占优是一个未解的难题.本文借助演化博弈理论,通过设置一定比例节点为指定策略作为控制手段,分别研究了在无结构群体和随机规则网络群体中的策略演化情况.在随机规则网络中,本文进一步研究了在控制手段下,一种新策略是如何演化并成功占据整个网络的.结果表明在无结构的情况下,强制策略对群体的影响受限于博弈的类型;而在随机规则网络中,在任何的博弈类型下,只要给定足够多的强制策略就可以使其突破成功.在理论分析的基础上,本文进行了计算机仿真验证,仿真结果与理论结果一致.本文的结果揭示了如何对群体施加影响,进而对群体中的个体状态进行控制. When the evolution of strategies in the network is studied through game theory, it is still an open question as to how to make a strategy to take over the whole network by exerting minimum control. In this paper, we investigate the evolution of strategies in unstructured networks and random regular networks by forcing a certain proportion of nodes' strategies as a control. Furthermore, in the random regular network, we have studied how a new strategy invades and succeeds in dominating the whole network under control. The results show that the effect of the forcing strategy in the unstructured group depends strongly on the type of game; however, in the random regular network and under any game type, the intrusion can be successful as long as a sufficient number of forcing strategies are given, which is validated by our simulation results.
作者 张建磊 李智琦 曹明 ZHANG Jian-lei;LI Zhi-qi;CAO Ming(College of Computer and Control Engineering,Nankai University,Tianjin 300350,China;Research Institute of Engineering and Technology,University of Groningen,Groningen 9747AG,Netherlands)
出处 《控制理论与应用》 EI CAS CSCD 北大核心 2018年第5期601-609,共9页 Control Theory & Applications
基金 中国国家自然科学基金项目(61603199 61603201) 荷兰国家自然科学基金项目(vidi–14134)资助~~
关键词 博弈论 随机规则网络 复制动力学 galne theory random regular network replicator dynamics
  • 相关文献

参考文献4

二级参考文献39

  • 1王先甲,全吉,刘伟兵.有限理性下的演化博弈与合作机制研究[J].系统工程理论与实践,2011,31(S1):82-93. 被引量:155
  • 2杨瑞龙,聂辉华.不完全契约理论:一个综述[J].经济研究,2006,41(2):104-115. 被引量:307
  • 3WANG Q F, GUAN Y P, WANG J" H. A chance-constrained two-stage stochastic program for unit commitment with uncertain wind power output [J]. IEEE Transactions on Power Systems, 2012, 27(1): 206 - 215. 被引量:1
  • 4WANG J H, SHAHIDEHPOUR M, LI Z Y. Security-constrained unit commitment with volatile wind power generation [J]. IEEE Transac- tions on Power Systems, 2008, 23(3): 1319 - 1327. 被引量:1
  • 5BERTSIMAS D, LITV1NOV E, SUN X A, et al. Adaptive robust op- timization for the security constrained unit commitment problem [J]. IEEE Transactions on Power Systems, 2013, 28(1): 52 - 63. 被引量:1
  • 6JIANG R W, WANG J H, GUAN Y E Robust unit commitment with wind power and pumped storage hydro [J]. IEEE Transactions on Power Systems, 2012, 27(2): 800 - 810. 被引量:1
  • 7WANG J, BOTTERUD A, BESSA R, et al. Wind power forecasting uncertainty and unit commitment [J]. Applied Energy, 2011, 88(11): 4014 - 4023. 被引量:1
  • 8KARANGELOS E, BOUFFARD F. A co-operative game theory approach to wind power generation imbalance cost allocation [EB/OL]. http: //www.pscc-central.org/uploads/tx_ethpublications/ fp42_01.pdf. 2011/2013. 被引量:1
  • 9梅生伟,刘锋,魏鞯.工程博弈论基础及其电力系统应用[M].北京:科学出版社,2015. 被引量:1
  • 10MEI S W, WANG Y Y, LIU F, et al. Game approaches for hybrid power system planning [J]. IEEE Transactions on Sustainable Ener- gy, 2012, 3(3): 506 - 517. 被引量:1

共引文献38

同被引文献24

引证文献3

二级引证文献3

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部