Extraction and utilization about knowledge in hierarchical interactive genetic algorithms
Dunwei Gong · Kongzhi yu juece · 2007
For the problem that interactive genetic algorithms lack a universal frame to utilize knowledge,a universal frame for extraction and utilization for knowledge in interactive genetic algorithms is proposed by adopting dual structure in culture algorithms.A knowledge model composed of common sense,evolution knowledge and evaluated knowledge is constructed,which describes implicit knowledge about users' cognitive and preference.Convergence is proved by using drift analysis,and critical generation substituting approximate model for users' evaluation are achieved.Based on fashion evolutionary design system,the rationality of this algorithm and the validity of the knowledge model are proved.Simulation results indicate that the algorithm can effectively alleviate users' fatigue and improve the speed of convergence.