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Reducing code bloat in Genetic Programming based on subtree substituting technique

Chu, T.H. and Nguyen, Q.U. (2017) Reducing code bloat in Genetic Programming based on subtree substituting technique. In: 21st Asia Pacific Symposium on Intelligent and Evolutionary Systems, IES 2017, 15 November 2017 through 17 November 2017.

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Abstract

Code bloat is a phenomenon in Genetic Programming (GP) that increases the size of individuals during the evolutionary process. Over the years, there has been a large number of research that attempted to address this problem. In this paper, we propose a new method to control code bloat and reduce the complexity of the solutions in GP. The proposed method is called Substituting a subtree with an Approximate Terminal (SAT-GP). The idea of SAT-GP is to select a portion of the largest individuals in each generation and then replace a random subtree in every individual in this portion by an approximate terminal of the similar semantics. SAT-GP is tested on twelve regression problems and its performance is compared to standard GP and the latest bloat control method (neat-GP). The experimental results are encouraging, SAT-GP achieved good performance on all tested problems regarding to the four popular performance metrics in GP research. © 2017 IEEE.

Item Type: Conference or Workshop Item (Paper)
Divisions: Faculties > Faculty of Information Technology
Identification Number: 10.1109/IESYS.2017.8233556
Uncontrolled Keywords: Codes (symbols); Genetic algorithms; Semantics; Code bloats; Control codes; Control methods; Evolutionary process; Performance metrics; Regression problem; Sub trees; Genetic programming
Additional Information: Conference code: 132093. Language of original document: English.
URI: http://eprints.lqdtu.edu.vn/id/eprint/9651

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