| 引用本文: | 郝国生,史有群,黄永青,吕俊怀,郭广颂.交互式进化计算的适应值噪声及收敛鲁棒性.软件学报,2007,18(9):2183-2193 |
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| 交互式进化计算的适应值噪声及收敛鲁棒性 |
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郝国生1,2, 史有群3, 黄永青1,4, 吕俊怀1, 郭广颂2,5
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1.徐州师范大学,计算机科学与技术学院,江苏,徐州,221116;2.中国矿业大学,信息与电气工程学院,江苏,徐州,221008;3.东华大学,计算机科学与技术学院,上海,200052;4.合肥工业大学,计算机网络系统研究所,安徽,合肥,230009;5.郑州航空工业管理学院,机电工程系,河南,郑州450007
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| 摘要: |
| 噪声是影响进化计算(evolutionary computation,简称EC)算法性能的一个重要因素.对于传统EC中的噪声,已有许多研究成果,但交互式进化计算(interactive evolutionary computation,简称IEC)的噪声研究成果却较少.首先回顾了传统EC中噪声的定义、来源、类型及各种处理噪声的方法;其次,从IEC的理性用户观点出发,研究了IEC的适应值噪声及收敛鲁棒性.其中,空间的映射关系、个体间的占优关系以及IEC的收敛等是研究收敛鲁棒性的两个定理(强条件定理和弱条件定理)的基础.这两个定理表明,理性用户条件下的噪声不会影响算法全局收敛性.在这两个定理的基础上进一步得出了如下结论:有效的适应度尺度变换是弱条件定理的一部分,IEC中"真"适应值是用户偏好等.并以不满足弱条件定理,即破坏算法收敛性为依据,给出了IEC中适应值噪声的狭义定义.实验进一步验证了这两个定理.上述结论为进一步研究IEC作了必要的铺垫. |
| 关键词: 进化计算 噪声 鲁棒 占优 收敛 |
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| 基金项目:Supported by the National Research Foundation for the Doctoral Program of Ministry of Education of China under Grant Nos.20050359006, 20040359004 (国家教育部博士点基金); the Shanghai Science Committee Foundation for the Mountaineering Action Plan under Grant No.06DZ15005 (上海市科委"登山行动计划"重大项目基金); the Xuzhou Normal University Research Foundation (徐州师范大学项目基金) |
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| Interactive Evolutionary Computation with Fitness Noise and Its Convergence Robustness |
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HAO Guo-Sheng,SHI You-Qun,HUANG Yong-Qing,Lü Jun-Huai,GUO Guang-Song
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| Abstract: |
| Noise is an important factor that influences the performance of evolutionary computation(EC).Much research on noise was reported in traditional EC,but less in IEC(interactive evolutionary computation).The definition,source,type of noise and methods to deal with noise in EC are reviewed firstly.Secondly,related with the rational user in IEC,the convergence robustness against fitness noise in IEC is studied.Mapping among spaces, dominating relationship and convergence in IEC are discussed to establish bases for two theorems:Strong condition theorem and weak condition theorem.These two theorems imply that the noise caused by the rational user will not prevent the algorithm from converging to the global optima.Thirdly,as the successive issue,the conclusions that the effective fitness scaling method is part of the weak condition and the user preference is the true fitness in IEC are discussed.The narrow definition of fitness noise based on the weak condition is also given.The experimental results validate the theorems,and the results establish a necessary foundation for future research. |
| Key words: evolutionary computation noise robustness domination convergence |
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