@inproceedings{952716b0dbaa463e8ea037afb6962072,
title = "An extended contract-net negotiation model based on task coalition and genetic algorithm",
abstract = "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.",
keywords = "Generic algorithm, Multi-agent system, Negotiation, Task allocation, Task coalition",
author = "Tao, \{Hai Jun\} and Wang, \{Ya Dong\} and Guo, \{Mao Zu\}",
year = "2007",
doi = "10.1109/ICMLC.2007.4370266",
language = "英语",
isbn = "142440973X",
series = "Proceedings of the Sixth International Conference on Machine Learning and Cybernetics, ICMLC 2007",
pages = "879--884",
booktitle = "Proceedings of the Sixth International Conference on Machine Learning and Cybernetics, ICMLC 2007",
note = "6th International Conference on Machine Learning and Cybernetics, ICMLC 2007 ; Conference date: 19-08-2007 Through 22-08-2007",
}