An extended contract-net negotiation model based on task coalition and genetic algorithm

被引:0
作者
Tao, Hai-Jun [1 ]
Wang, Ya-Dong [1 ]
Guo, Viao-Zu [1 ]
机构
[1] Harbin Inst Technol, Sch Comp Sci & Technol, Harbin 150001, Peoples R China
来源
PROCEEDINGS OF 2007 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-7 | 2007年
关键词
multi-agent system; negotiation; task coalition; generic algorithm; task allocation;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Multi-agent negotiation has been one of the key problems in the multi-agent research area. An extended contract-net negotiation model based on task coalition and genetic algorithm is presented after analyzing the advantage and disadvantage of the classical contract-net negotiation model. Formalized definition method and coalition generation algorithm are given. A specialized genetic algorithm, which is optimized by optimized initial colony selection, optimized parent crossover/mutation and the using of Metropolis rule, is used to solve the task allocation in the coalition. The algorithm improves the efficiency of task allocation and reduces the communication cost. By testing and analyzing an example of a missile defense system, it is proved that the model can reduce the negotiation cost effectively contrast with the classical contract-net model on the basis of ensuring the negotiation quality.
引用
收藏
页码:879 / 884
页数:6
相关论文
共 50 条
[31]   MULTI-UAV Task Allocation Based on Improved Genetic Algorithm [J].
Wu, Xueli ;
Yin, Yanan ;
Xu, Lei ;
Wu, Xiaojing ;
Meng, Fanhua ;
Zhen, Ran .
IEEE ACCESS, 2021, 9 :100369-100379
[32]   A hybrid algorithm based on PSO and GA to dynamic virtual holon mechanism and negotiation model [J].
Zhao, Fuqing ;
Zhang, Qiuyu ;
Wang, Lianxiang .
PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEMS AND KNOWLEDGE ENGINEERING (ISKE 2007), 2007,
[33]   Multi-Granular Genetic Algorithm Based Task Allocation for Heterogeneous UAVs [J].
Cao, Jiajia ;
Wang, Guoyin ;
Liu, Qun ;
Jiang, Haihuan .
2024 10TH INTERNATIONAL CONFERENCE ON BIG DATA AND INFORMATION ANALYTICS, BIGDIA 2024, 2024, :1-8
[34]   Multi-Robot Task Allocation Based On Robotic Utility Value and Genetic Algorithm [J].
Chen Jianping ;
Yang Yumin ;
Wu Yunbiao .
2009 IEEE INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTING AND INTELLIGENT SYSTEMS, PROCEEDINGS, VOL 2, 2009, :256-260
[35]   Genetic Algorithm Based Combinatorial Auction Method for Multi-Robot Task Allocation [J].
龚建伟 ;
黄宛宁 ;
熊光明 ;
满益明 .
Journal of Beijing Institute of Technology(English Edition), 2007, (02) :151-156
[36]   Task Allocation Optimization in Collaborative Customized Product Development Based on Adaptive Genetic Algorithm [J].
Bao, Beifang ;
Yang, Yu ;
Liu, Aijun ;
Zhao, Jiali ;
Li, Leiting .
JOURNAL OF INTELLIGENT SYSTEMS, 2014, 23 (01) :1-19
[37]   Multi-UAVs collaborative task allocation based on genetic slime mould algorithm in battlefield environment [J].
Xue, Yali ;
Li, Hanyan ;
Ouyang, Quan ;
Cui, Shan ;
Hong, Jun .
Zhejiang Daxue Xuebao (Gongxue Ban)/Journal of Zhejiang University (Engineering Science), 2024, 58 (08) :1748-1756
[38]   Research on Multi-robot Task Allocation Based on BP Neural Network Optimized by Genetic Algorithm [J].
Dai, Xuefeng ;
Wang, Jiazhi ;
Zhao, Jianqi .
2018 5TH INTERNATIONAL CONFERENCE ON INFORMATION SCIENCE AND CONTROL ENGINEERING (ICISCE 2018), 2018, :478-481
[39]   Centralized multi-robot logistic system: An approach using the island model genetic algorithm as task scheduler [J].
Cechinel, Alan Kunz ;
De Pieri, Edson Roberto .
INTERNATIONAL JOURNAL OF ADVANCED ROBOTIC SYSTEMS, 2024, 21 (05)
[40]   Inverse Preference Optimization in the Graph Model for Conflict Resolution based on the Genetic Algorithm [J].
Tao, Liangyan ;
Su, Xuebi ;
Javed, Saad Ahmed .
GROUP DECISION AND NEGOTIATION, 2021, 30 (05) :1085-1112