Abstract
In this paper, we show that NSGA-II can be applied to GP and the Process Description Language (PDL) and describe two modifications to NSGA-II. The first modification removes individuals which have the same behaviour from GP populations. It selects for de-duplication by taking the result of each objective fitness function together to make a comparison. NSGA-II is designed to expand its Pareto front of solutions by favouring individuals who have the highest or lowest value (boundary points) in a front, for any objective. The second modification enhances exploitation by preferring individuals who occupy an extreme position for most objective fitness functions. The results show, for the first time, that NSGA-II can be used with PDL and GP to successfully solve a robot control problem and that the suggested modifications offer significant improvements over an algorithm used previously with GP and PDL and unmodified NSGA-II for our test problem.
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Shannon, P.D., Nehaniv, C.L., Phon-Amnuaisuk, S. (2017). Enhancing Exploration and Exploitation of NSGA-II with GP and PDL. In: Tan, Y., Takagi, H., Shi, Y. (eds) Advances in Swarm Intelligence. ICSI 2017. Lecture Notes in Computer Science(), vol 10385. Springer, Cham. https://doi.org/10.1007/978-3-319-61824-1_38
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DOI: https://doi.org/10.1007/978-3-319-61824-1_38
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