An Adaptive Genetic Algorithm and Its Application to Multi-literal Multi-issue Competitive E-commerce
一种竞争环境下基于自适应遗传算法的多边多议题协商

To make the agents negotiate more efficiently in multi-lateral multi-issue negotiation in multi-agent based competitive e-commerce, an agent negotiation model in competitive environment is presented, and the Adaptive Genetic Algorithm(AGA) is applied to the model to enhance the negotiation efficiency. In the experiments, two kinds of genetic algorithms are used to compare with, they are Standard Genetic Algorithm(SGA) and AGA. After 1000 times of experiments for the two kinds of agents to gain the satisfying result, SGA averagely needs negotiation of 183 runs, while the AGA averagely needs only 152 runs. The experiment results show that the AGA can gain the satisfying negotiation result more efficiently than SGA in competitive multi-lateral multi-issue negotiation.