Home
This Title All WIREs
WIREs RSS Feed
How to cite this WIREs title:
WIREs Data Mining Knowl Discov
Impact Factor: 2.111

Swarm‐based metaheuristics in automatic programming: a survey

Full article on Wiley Online Library:   HTML PDF

Can't access this content? Tell your librarian.

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. WIREs Data Mining Knowl Discov 2014, 4:445–469. doi: 10.1002/widm.1138

Conflict of interest: The authors have declared no conflicts of interest for this article.

Swarm‐based automatic programming publications per year.
[ Normal View | Magnified View ]
Two sample artificial fish individuals with the same structure.
[ Normal View | Magnified View ]
Artificial bee colony programming (ABCP) sharing mechanism.
[ Normal View | Magnified View ]
An example of the genotype–phenotype mapping in grammatical swarm (GS) from a linear chromosome. The integer values are used to select production rules of the context‐free grammar (CFG), producing a derivation sequence that can be kept as a derivation tree, which is further decoded to an expression tree.
[ Normal View | Magnified View ]
Part of the derivation tree explored by ants to generate an expression in generalized ant programming (GAP).
[ Normal View | Magnified View ]
Tree structure generated from a graph in the ant colony programming (ACP) expression approach.
[ Normal View | Magnified View ]
Prototype tree with a pheromone table associated with each node (it is shown only for the first two nodes).
[ Normal View | Magnified View ]
Percentage of swarm‐based automatic programming publications by metaheuristic.
[ Normal View | Magnified View ]

Browse by Topic

Technologies > Classification
Technologies > Computational Intelligence
Algorithmic Development
Technologies
Algorithmic Development > Association Rules

Access to this WIREs title is by subscription only.

Recommend to Your
Librarian Now!

The latest WIREs articles in your inbox

Sign Up for Article Alerts