Chu, T.H. and Nguyen, Q.U. and Cao, V.L. (2018) Semantics based substituting technique for reducing code bloat in genetic programming. In: 9th International Symposium on Information and Communication Technology, SoICT 2018, 6 December 2018 through 7 December 2018.
Reducing code bloat in Genetic Programming based on subtree substituting technique..pdf
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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 characterized 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. © 2018 Association for Computing Machinery.
Item Type: | Conference or Workshop Item (Paper) |
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Divisions: | Faculties > Faculty of Information Technology |
Identification Number: | 10.1145/3287921.3287948 |
Uncontrolled Keywords: | Codes (symbols); Genetic algorithms; Problem solving; Semantics; Time series; Trees (mathematics); Code bloats; Code growth; Control methods; Parameter setting; Performance metrics; Real-world time series; Sub trees; Tree structures; Genetic programming |
Additional Information: | Conference code: 143217. Language of original document: English. |
URI: | http://eprints.lqdtu.edu.vn/id/eprint/9489 |