- author = "Thi Huong Chu and Quang Uy Nguyen and Van Loi Cao",
- title = "Semantics Based Substituting Technique for Reducing Code Bloat in Genetic Programming",
- booktitle = "Proceedings of the Ninth International Symposium on Information and Communication Technology, SoICT 2018",
- year = "2018",
- pages = "77--83",
- address = "Danang City, Viet Nam",
- month = dec # " 6-7",
- publisher = "ACM",
- keywords = "genetic algorithms, genetic programming, code growth, code bloat, semantics, time series",
- isbn13 = "978-1-4503-6539-0",
- acmid = "3287948",
- bibsource = "DBLP, http://dblp.uni-trier.de/db/conf/soict/soict2018.html#ChuNC18",
-
URL = "
http://doi.acm.org/10.1145/3287921.3287948",
-
DOI = "
doi:10.1145/3287921.3287948",
- abstract = "Genetic Programming (GP) is a technique that allows computer programs encoded as a set of tree structures to be evolved using an evolutionary algorithm. In GP, code bloat is a common phenomenon characterised by the size of individuals gradually increasing during the evolution. This phenomenon has a negative impact on GP performance in solving problems. In order to address this problem, we have recently introduced a code bloat control method based on semantics: Substituting a subtree with an Approximate Terminal (SAT-GP). In this paper, we propose an extension of SAT-GP, namely Substituting a subtree with an Approximate Subprogram (SAS-GP). We tested this method with different GP parameter settings on a real-world time series forecasting problem. The experimental results demonstrate the benefit of the proposed method in reducing the code bloat phenomenon and improving GP performance. Particularly, SAS-GP often achieves the best performance compared to other tested GP systems using four popular performance metrics in GP.",
-
notes = "Le Quy Don Technical University, Hanoi, Vietnam
also known as \cite{conf/soict/ChuNC18}",
