Theoretical results in genetic programming: the next ten years?

被引：0
|
作者：
Riccardo Poli
Leonardo Vanneschi
William B. Langdon
Nicholas Freitag McPhee
机构：
[1] University of Essex,School of Computer Science and Electronic Engineering
[2] University of Milano-Bicocca,Department of Informatics, Systems and Communication (D.I.S.Co.)
[3] King’s College London,Department of Computer Science
[4] University of Minnesota Morris,Division of Science and Mathematics
来源：
Genetic Programming and Evolvable Machines | 2010年 / 11卷
关键词：
Genetic programming; Theory; Challenges; Open problems;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
We consider the theoretical results in GP so far and prospective areas for the future. We begin by reviewing the state of the art in genetic programming (GP) theory including: schema theories, Markov chain models, the distribution of functionality in program search spaces, the problem of bloat, the applicability of the no-free-lunch theory to GP, and how we can estimate the difficulty of problems before actually running the system. We then look at how each of these areas might develop in the next decade, considering also new possible avenues for theory, the challenges ahead and the open issues.
引用
收藏
页码：285 / 320
页数：35
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