交互式遗传算法的机器代替用户方法

Method of Replacing the User with Machine in Interactive Genetic Algorithm

如何让无疲劳的计算机代替易疲劳的用户是交互式遗传算法研究的一个重要内容.本文首先研究了机器代替用户的3个基本内容,即,机器代替用户扮演环境角色,对个体进行评价;机器采样和代替用户的时机是进入偏好稳定阶段;机器寻优结果由样本和代替用户策略决定.其次,给出基于基因意义单元"适应值"估计的个体适应值估计方法.最后,通过比较实验验证了本文方法的有效性.

It is an important to replace a user with the machine in interactive algorithm , because compared with tireless machine, a user is apt to be tired. Firstly, three basic viewpoints are put forward . The first viewpoint is that the machine plays the role of environment to select the individual. The second is that the chance for machine＇s sampling and replacing user should be in the phase during which a user＇s preference doesn^s fluctuate again. The third is that the result of optimization is determined by the sampling data and the strategies that the machine applies. Next , the individual fitness estimation method based on gene - sense - unit fitness is given . Its efficiency is validated by comparative experiment.