Grammar-based Genetic Programming: a survey

被引:0
作者
Robert I. McKay
Nguyen Xuan Hoai
Peter Alexander Whigham
Yin Shan
Michael O’Neill
机构
[1] Seoul National University,Structural Complexity Lab, School of Computer Science and Engineering
[2] Le Quy Don University,Department of Computer Science
[3] University of Otago,Department of Information Science
[4] Medicare Australia,Complex and Adaptive Systems Lab, School of Computer Science and Informatics
[5] University College Dublin,undefined
来源
Genetic Programming and Evolvable Machines | 2010年 / 11卷
关键词
Genetic programming; Evolutionary computation; Grammar; Context free; Regular; Tree adjoining;
D O I
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中图分类号
学科分类号
摘要
Grammar formalisms are one of the key representation structures in Computer Science. So it is not surprising that they have also become important as a method for formalizing constraints in Genetic Programming (GP). Practical grammar-based GP systems first appeared in the mid 1990s, and have subsequently become an important strand in GP research and applications. We trace their subsequent rise, surveying the various grammar-based formalisms that have been used in GP and discussing the contributions they have made to the progress of GP. We illustrate these contributions with a range of applications of grammar-based GP, showing how grammar formalisms contributed to the solutions of these problems. We briefly discuss the likely future development of grammar-based GP systems, and conclude with a brief summary of the field.
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页码:365 / 396
页数:31
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