Paper Info
Title
On the architecture and implementation of tree-based genetic programming in HeuristicLab
Abstract
This article describes the architecture and implementation of the genetic programming (GP) framework of HeuristicLab. In particular we focus on the core design goals, namely extensibility, usability, and performance optimization and explain our approach to reach these goals. The overall design, the encoding, interpretation, and evaluation of programs is described and code examples are given to explain core aspects of the framework. HeuristicLab is available as open source software at http://dev.heuristiclab.com.
Year
DOI
Venue
2012
10.1145/2330784.2330801
GECCO (Companion)
Keywords
Field
DocType
open source software,overall design,tree-based genetic programming,performance optimization,genetic programming,core aspect,code example,core design goal
Architecture,Programming language,Computer science,Usability,Genetic programming,Symbolic regression,Open source software,Extensibility,Encoding (memory)
Conference
Citations 
PageRank 
References 
7
0.89
8
Authors
5
Name
Order
Citations
PageRank
Michael Kommenda19715.58
Gabriel Kronberger219225.40
Stefan Wagner317227.06
Stephan Winkler412013.85
Michael Affenzeller533962.47