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Leroux, Claris; Otero, Fernando E.B.; Johnson, Colin G. (2014)
Languages: English
Types: Unknown
Subjects: Q335
There are many different genetic programming (GP) frameworks that can be used to implement algorithms to solve a particular optimization problem. In order to use a framework, users need to become familiar with a large numbers of source code before actually implementing the algorithm, adding a learning overhead. In some cases, this can prevent users from trying out different frameworks. This paper discusses the implementation of a code generator in the EpochX framework to facilitate the implementation of GP algorithms. The code generator is based on the GP defini- tion language (GPDL), which is a framework-independent language that can be used to specify GP problems.
  • The results below are discovered through our pilot algorithms. Let us know how we are doing!

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    • [6] F. Otero, T. Castle, and C. G. Johnson. Epochx: Genetic programming in java with statistics and event monitoring. In GECCO'12 Companion, Philadelphia, PA, USA, July 2012.
    • [7] L. Vaseux, F. Otero, T. Castle, and C. G. Johnson. Event-based graphical monitoring in the epochx genetic programming framework. In GECCO'13 Companion, Amsterdam, The Netherlands, July 2013.
    • [8] S. Wagner. Heuristic Optimization Software Systems - Modeling of Heuristic Optimization Algorithms in the HeuristicLab Software Environment. PhD thesis, Institute for Formal Models and Verification, Johannes Kepler University Linz, Austria, 2009.
    • [9] P. Whigham. Grammatically-based genetic programming. In Proceedings of the Workshop on Genetic Programming: From Theory to Real-World Applications, pages 33-41, 1995.
  • No related research data.
  • Discovered through pilot similarity algorithms. Send us your feedback.

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