[1]吴虎胜,肖人彬.群智能新研究：角色?匹配的狼群劳动分工[J].智能系统学报,2021,16(1):125-133.[doi:10.11992/tis.202007043]
WU Husheng,XIAO Renbin.A new approach to swarm intelligence: role-matching labor division of a wolf pack[J].CAAI Transactions on Intelligent Systems,2021,16(1):125-133.[doi:10.11992/tis.202007043]
点击复制
WU Husheng,XIAO Renbin.A new approach to swarm intelligence: role-matching labor division of a wolf pack[J].CAAI Transactions on Intelligent Systems,2021,16(1):125-133.[doi:10.11992/tis.202007043]
群智能新研究：角色?匹配的狼群劳动分工
《智能系统学报》[ISSN 1673-4785/CN 23-1538/TP] 卷:
16
期数:
2021年第1期
页码:
125-133
栏目:
学术论文—人工智能基础
出版日期:
2021-01-05
- Title:
- A new approach to swarm intelligence: role-matching labor division of a wolf pack
- Keywords:
- swarm intelligence; wolf pack; labor division; task allocation; self-organization; role-matching; activation-inhibition; stimulus-response
- 分类号:
- TP242
- 摘要:
- 启发于生物狼群群体的劳动分工行为，本文提出一种新颖的角色?匹配狼群劳动分工方法。通过剖析自然狼群的生物学行为，概括提炼出狼群劳动分工行为的个体任务的专职化、个体角色可塑性和任务分配均衡性3个典型特征，并建立了生物狼群劳动分工行为与普适性任务分配问题之间的仿生映射关系；从狼群“个体?个体”+“个体?环境”的交互方式角度出发，分析了角色?匹配的狼群劳动分工的个体角色转换和任务调整机制，研究了狼群角色?匹配的柔性劳动分工机制，提出了一种新的群智能方法，即角色?匹配的狼群劳动分工方法；将狼群的角色?匹配劳动分工与蚁群的刺激?响应劳动分工和蜂群的激发?抑制劳动分工进行了比较分析，并展示出角色?匹配狼群劳动分工方法的应用前景。
- Abstract:
- A novel role-matching labor division method is proposed, inspired by the labor division behavior of a biological wolf pack. First, through in-depth analysis of the biological behavior of natural wolves, the three typical characteristics of the labor division behavior of a wolf pack, i.e., the specialization of individual tasks, the plasticity of individual roles, and the balance of task allocation, are summarized and analyzed in this paper. The bionic mapping relationship between the labor division behavior of a biological wolf pack and the universal task allocation is established. Second, from the perspective of the interactive mode of “individual-individual” plus “individual-environment,” the individual role transformation and task adjustment mechanism of the role-matching labor division of a wolf pack are analyzed deeply in this paper. The flexible role-matching labor division mechanism of a wolf pack is studied, and a new swarm intelligence method is proposed, i.e., the wolf pack role-matching labor division method. Finally, the wolf pack role-matching labor division model, ant colony stimulus-response labor division model, and bee colony activation-inhibition labor division model are compared and analyzed, the proposed method has extensive application prospects in many fields.
- 参考文献/References:
-
[1] ROBINSON G E. Regulation of division of labor in insect societies[J]. Annual review of entomology, 1992, 37(1):637-665.
[2] XIAO Renbin, WANG Yingcong. Labour division in swarm intelligence for allocation problems:a survey[J]. International journal of bio-inspired computation, 2018, 12(2):71-86.
[3] 肖人彬, 王英聪. 群智能自组织劳动分工研究进展[J]. 信息与控制, 2019, 48(2):129-139, 148
XIAO Renbin, WANG Yingcong. Research progress of self-organized labor division in swarm intelligence[J]. Information and control, 2019, 48(2):129-139, 148
[4] PARPINELLI R S, LOPES H S. New inspirations in swarm intelligence:a survey[J]. International journal of bio-inspired computation, 2011, 3(1):1-16.
[5] BESHERS S N, FEWELL J H. Models of division of labor in social insects[J]. Annual review of entomology, 2001, 46(1):413-440.
[6] 王伟嘉, 郑雅婷, 林国政, 等. 集群机器人研究综述[J]. 机器人, 2020, 42(2):232-256
WANG Weijia, ZHENG Yating, LING Guozheng, et al. Swarm robotics:a review[J]. Robot, 2020, 42(2):232-256
[7] TAN Ying, ZHENG Zhongyang. Research advance in swarm robotics[J]. Defence technology, 2013, 9(1):18-39.
[8] KORSAH G A, STENTZ A, DIAS M B. A comprehensive taxonomy for multi-robot task allocation[J]. The international journal of robotics research, 2013, 32(12):1495-1512.
[9] KHAMIS A, HUSSEIN A, ELMOGY A. Multi-robot task allocation:a review of the state-of-the-art[M]. KOUB?A A, MARTíNEZ-DE DIOS J. Cooperative Robots and Sensor Networks 2015. Studies in Computational Intelligence. Cham, Germany:Springer, 2015.
[10] LIU Chun, KROLL A. Performance impact of mutation operators of a subpopulation-based genetic algorithm for multi-robot task allocation problems[J]. SpringerPlu, 2016, 5(1):1361.
[11] GERKEY B P, MATARI? M J. A formal analysis and taxonomy of task allocation in multi-robot systems[J]. The international journal of robotics research, 2004, 23(9):939-954.
[12] WANG Jianping, GU Yuesheng, LI Xiaomin. Multi-robot task allocation based on ant colony algorithm[J]. Journal of computers, 2012, 7(9):2160-2167.
[13] LI Hao, XIAO Renbin, WU Husheng. Modelling for combat task allocation problem of aerial swarm and its solution using wolf pack algorithm[J]. International journal of innovative computing and applications, 2016, 7(1):50-59.
[14] BENI G. From swarm intelligence to swarm robotics[M]. SAHIN E, SPEARS W M. Swarm Robotics. Berlin, Heidelberg:Springer, 2004:1-9.
[15] MECH D L. Alpha status, dominance, and division of labor in wolf packs[J]. Canadian journal of zoology, 1999, 77(8):1196-1203.
[16] 吴虎胜, 张凤鸣, 吴庐山. 一种新的群体智能算法-狼群算法[J]. 系统工程与电子技术, 2013, 35(11):2430-2438
WU Husheng, ZHANG Fengming, WU Lushan. A new swarm intelligence algorithm-wolf pack algorithm[J]. Systems engineering and electronics, 2013, 35(11):2430-2438
[17] MIRJALILI S, MIRJALILI S M, LEWIS A. Grey wolf optimizer[J]. Advances in engineering software, 2014, 69:46-61.
[18] PIEREZAN J, COELHO L D S. Coyote optimization algorithm:a new metaheuristic for global optimization problems[C]//Proceedings of 2018 IEEE Congress on Evolutionary Computation (CEC). Rio de Janeiro, Brazil:IEEE, 2018.
[19] WU Husheng, XIAO Renbin. Flexible wolf pack algorithm for dynamic multidimensional knapsack problems[J]. Research, 2020, 2020:1762107.
[20] MADDEN J D, ARKIN R C, MACNULTY D R. Multi-robot system based on model of wolf hunting behavior to emulate wolf and elk interactions[C]//Proceedings of 2010 IEEE International Conference on Robotics and Biomimetics. Tianjin, China:IEEE, 2010.
[21] MARTíN J, BARJA I, LóPEZ P. Chemical scent constituents in feces of wild Iberian wolves (Canis lupus signatus)[J]. Biochemical systematics and ecology, 2010, 38(6):1096-1102.
[22] NOWAK S, J?DRZEJEWSKI W, SCHMIDT K, et al. Howling activity of free-ranging wolves (Canis lupus) in the Bia?owie?a primeval forest and the western Beskidy Mountains (Poland)[J]. Journal of ethology, 2007, 25(3):231-237.
[23] HEBERLEIN M T E, TURNER D C, RANGE F, et al. A comparison between wolves, Canis lupus, and dogs, Canis familiaris, in showing behaviour towards humans[J]. Animal behaviour, 2016, 122:59-66.
[24] WHITE K A J, LEWIS M A, MURRAY J D. A model for wolf-pack territory formation and maintenance[J]. Journal of theoretical biology, 1996, 178(1):29-43.
[25] WU Husheng, ZHANG Fengming. A uncultivated wolf pack algorithm for high-dimensional functions and its application in parameters optimization of PID controller[C]//Proceedings of the 2014 IEEE Congress on Evolutionary Computation. Beijing, China:IEEE, 2014:1477-1482.
[26] BONABEAU E, THERAULAZ G, DENEUBOURG J L. Quantitative study of the fixed threshold model for the regulation of division of labour in insect societies[J]. Proceedings of the royal society of London. series B:biological sciences, 1996, 263(1376):1565-1569.
[27] BESHERS S N, HUANG Z Y, OONO Y, et al. Social inhibition and the regulation of temporal polyethism in honey bees[J]. Journal of theoretical biology, 2001, 213(3):461-479.
[28] DUARTE A, PEN I, KELLER L, et al. Evolution of self-organized division of labor in a response threshold model[J]. Behavioral ecology and sociobiology, 2012, 66(6):947-957.
[29] 胡亮. 基于激发抑制的群智能劳动分工方法求解动态分配问题[D]. 武汉:华中科技大学, 2019.
HU Liang. Solving dynamic allocation problems by activator-inhibitor based labor division approach in swarm intelligence[D]. Wuhan:Huazhong University of Science and Technology, 2019.
[30] WU Husheng, LI Hao, XIAO Renbin, et al. Modeling and simulation of dynamic ant colony’s labor division for task allocation of UAV swarm[J]. Physica A:statistical mechanics and its applications, 2018, 491:127-141.
[31] 肖人彬, 王英聪. 一种面向时间分配问题的群智能劳动分工新方法[J]. 智能系统学报, 2019, 14(3):438-448
XIAO Renbin, WANG Yingcong. A new approach to labor division in swarm intelligence for time allocation problem[J]. CAAI transactions on intelligent systems, 2019, 14(3):438-448
[32] WANG Yingcong, XIAO Renbin, WANG Huimin. A flexible labour division approach to the polygon packing problem based on space allocation[J]. International journal of production research, 2017, 55(11):3025-3045.
[33] 曹勇, 肖人彬. 蜂群激发抑制与刺激响应相结合的群机器人区域覆盖算法[J]. 复杂系统与复杂性科学, 2019, 16(4):1-12
CAO Yong, XIAO Renbin. Swarm robot region coverage algorithm combined with bee colony activator inhibition with stimulus response[J]. Complex systems and complexity science, 2019, 16(4):1-12
- 相似文献/References:
-
[1]莫宏伟.自然计算研究进展[J].智能系统学报,2011,6(6):544.
MO Hongwei.Research advance on natural computing[J].CAAI Transactions on Intelligent Systems,2011,6():544.
[2]李素,袁志高,王聪,等.群智能算法优化支持向量机参数综述[J].智能系统学报,2018,13(1):70.[doi:10.11992/tis.201707011]
LI Su,YUAN Zhigao,WANG Cong,et al.Optimization of support vector machine parameters based on group intelligence algorithm[J].CAAI Transactions on Intelligent Systems,2018,13():70.[doi:10.11992/tis.201707011]
[3]肖人彬,王英聪.一种面向时间分配问题的群智能劳动分工新方法[J].智能系统学报,2019,14(3):438.[doi:10.11992/tis.201807014]
XIAO Renbin,WANG Yingcong.A new approach to labor division in swarm intelligence for time allocation problem[J].CAAI Transactions on Intelligent Systems,2019,14():438.[doi:10.11992/tis.201807014]
备注/Memo
收稿日期:2020-07-24。
基金项目:科技创新 2030—“新一代人工智能”重大项目 (2018AAA0101200)；国家自然科学基金项目(61502534)；国家社科基金军事学项目(2019-SKJJ-C-092)；陕西省自然科学基金项目(2020JQ-493)；武警工程大学基础理论研究基金项目(WJY201922)
作者简介:吴虎胜，副教授，主要研究方向为群智能、无人系统及其作战运用、军事装备论证。主持国家自然科学基金、军内装备科研等省部级以上项目10余项。发表学术论文 30 余篇;肖人彬，教授，博士生导师，主要研究方向为群智能、涌现计算、复杂系统建模与仿真。主持国家级项目多项，获得教育部、湖北省自然科学奖和科技进步奖 5 项。发表学术论文 200余篇，入选 Elsevier “中国高被引学者”榜单
通讯作者:肖人彬. E-mail：rbxiao@hust.edu.cn
更新日期/Last Update:
2021-02-25