Swarm-based metaheuristics in automatic programming: a survey

被引:13
|
作者
Olmo, Juan L. [1 ]
Romero, Jose R. [1 ]
Ventura, Sebastian [1 ,2 ]
机构
[1] Univ Cordoba, Dept Comp Sci & Numer Anal, Cordoba, Spain
[2] King Abdulaziz Univ, Dept Comp Sci, Jeddah 21413, Saudi Arabia
关键词
ANT COLONY OPTIMIZATION; GRAMMATICAL SWARM; NEURAL-NETWORKS; BEE BEHAVIOR; CLASSIFICATION; ALGORITHM; SYSTEM; INTELLIGENCE; CONSTRUCTION; GENERATION;
D O I
10.1002/widm.1138
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
On the one hand, swarm intelligence (SI) is an emerging field of artificial intelligence that takes inspiration in the collective and social behavior of different groups of simple agents. On the other hand, the automatic evolution of programs is an active research area that has attracted a lot of interest and has been mostly promoted by the genetic programming paradigm. The main objective is to find computer programs from a high-level problem statement of what needs to be done, without needing to know the structure of the solution beforehand. This paper looks at the intersection between SI and automatic programming, providing a survey on the state-of-the-art of the automatic programming algorithms that use an SI metaheuristic as the search technique. The expression of swarm programming (SP) has been coined to cover swarm-based automatic programming proposals, since they have been published to date in a disorganized manner. Open issues for future research are listed. Although it is a very recent area, we hope that this work will stimulate the interest of the research community in the development of new SP metaheuristics, algorithms, and applications. (C) 2014 John Wiley & Sons, Ltd.
引用
收藏
页码:445 / 469
页数:25
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