Initialisation and grammar design in grammar-guided evolutionary computation
Grant Dick, Peter A. Whigham · Proceedings of the Genetic and Evolutionary Computation Conference Companion · 2022
Grammars provide a convenient and powerful mechanism to define the space of possible solutions for a range of problems. While recent work has shed light on the matters of initialisation and grammar design with respect to grammatical evolution (GE), their impact on other methods, such as random search and context-free grammar genetic programming (CFG-GP), is largely unknown. This paper examines GE, random search and CFG-GP on benchmark problems using different initialisation routines and grammar designs. Results suggest that CFG-GP is less sensitive to initialisation and grammar design than both GE and random search: we also demonstrate that observed cases of poor performance by CFG-GP are managed through simple adjustment of tuning parameters. We conclude that CFG-GP is a strong base from which to conduct grammar-guided evolutionary search, and that future work should focus on understanding the parameter space of CFG-GP for better application.