摘要
遗传规划 (GP)是一种关于产生问题解的计算机程序或者其他复杂结构的自动方法。它被成功地应用于自动设计、模式识别、机器人控制、神经网络结构的合成、符号回归、音乐和图像产生等难题。本文描述了遗传规划中的基本算法、理论及各种改进方法 ,讨论了遗传规划的关键技术 ,介绍了一些典型的实现系统及主要的应用领域 。
Genetic programming(GP) is an automatic method for creating a computer programming or other complex structure solve a problem. It has been applied successfully to a large number of difficult problems like automatic design, pattern recognition, robotic control, synthesis on neural architectures, symbolic regression, music and picture generation. In this paper, the basic algorithms, their theory and many improvement methods are described. Some important techniques about GP are discussed, and some typical GP systems and their main applications are also introduced. Also some new devleopment trends concerning genetic programming are proposed.
出处
《浙江工业大学学报》
CAS
2003年第2期153-159,168,共8页
Journal of Zhejiang University of Technology
基金
国家自然科学基金资助项目 (5 0 175 10 3)
国家 86 3计划项目 (2 0 0 2 AA4 12 6 10 )
浙江省科技计划重点项目(2 0 0 3C2 10 0 5 )资助
