Abstract
In this paper, we present a Matlab version of libGE. libGE is a famous library for Grammatical Evolution (GE). GE was proposed initially in [1] as a tool for automatic programming. Ever since then, GE has been widely successful in innovation and producing human-competitive results for various types of problems. However, its implementation in C++ (libGE) was somewhat prohibitive for a wider range of scientists and engineers. libGE requires several tweaks and integrations before it can be used by anyone. For anybody who does not have a background in computer science, its usage could be a bottleneck. This prompted us to find a way to bring it to Matlab. Matlab, as it is widely known, is a fourth generation programming language used for numerical computing. Details aside, but it is well known for its user-friendliness in the wider research community. By bringing GE to Matlab, we hope that many researchers across the world shall be able to use it, despite their academic background. We call our implementation of GE as GELAB. GELAB is currently present online as an open-source software (https://github.com/adilraja/GELAB). It can be readily used in research and development.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
Notes
- 1.
Web: http://bds.ul.ie/libGE/.
References
O’Neill, M., Ryan, C.: Grammatical evolution. IEEE Trans. Evol. Comput. 5, 349–358 (2001)
Müller, V.C., Bostrom, N.: Future progress in artificial intelligence: a survey of expert opinion. In: Müller, V.C. (ed.) Fundamental Issues of Artificial Intelligence. SL, vol. 376, pp. 553–570. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-26485-1_33
Mitchell, T.: Machine Learning. McGraw Hill, New York (1997)
Raja, M.A., Rahman, S.U.: A tutorial on simulating unmanned aerial vehicles. In: 2017 International Multi-topic Conference (INMIC), pp. 1–6 (2017)
Habib, S., Malik, M., Rahman, S.U., Raja, M.A.: NUAV - a testbed for developing autonomous unmanned aerial vehicles. In: 2017 International Conference on Communication, Computing and Digital Systems (C-CODE), pp. 185–192 (2017)
Raja, M.A., Ali, S., Mahmood, A.: Simulators as drivers of cutting edge research. In: 2016 7th International Conference on Intelligent Systems, Modelling and Simulation (ISMS), pp. 114–119 (2016)
Keijzer, M.: Scaled symbolic regression. Genet. Program. Evolvable Mach. 5, 259–269 (2004)
Raja, A., Flanagan, C.: Real-time, non-intrusive speech quality estimation: a signal-based model. In: O’Neill, M., et al. (eds.) EuroGP 2008. LNCS, vol. 4971, pp. 37–48. Springer, Heidelberg (2008). https://doi.org/10.1007/978-3-540-78671-9_4
Harik, G.R., Lobo, F.G., Goldberg, D.E.: The compact genetic algorithm. IEEE Trans. Evol. Comput. 3, 287–297 (1999)
Mininno, E., Cupertino, F., Naso, D.: Real-valued compact genetic algorithms for embedded microcontroller optimization. IEEE Trans. Evol. Comput. 12, 203–219 (2008)
Keijzer, M.: Alternatives in subtree caching for genetic programming. In: Keijzer, M., O’Reilly, U.-M., Lucas, S., Costa, E., Soule, T. (eds.) EuroGP 2004. LNCS, vol. 3003, pp. 328–337. Springer, Heidelberg (2004). https://doi.org/10.1007/978-3-540-24650-3_31
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Nature Switzerland AG
About this paper
Cite this paper
Raja, M.A., Ryan, C. (2018). GELAB - A Matlab Toolbox for Grammatical Evolution. In: Yin, H., Camacho, D., Novais, P., Tallón-Ballesteros, A. (eds) Intelligent Data Engineering and Automated Learning – IDEAL 2018. IDEAL 2018. Lecture Notes in Computer Science(), vol 11315. Springer, Cham. https://doi.org/10.1007/978-3-030-03496-2_22
Download citation
DOI: https://doi.org/10.1007/978-3-030-03496-2_22
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-03495-5
Online ISBN: 978-3-030-03496-2
eBook Packages: Computer ScienceComputer Science (R0)