Abstract
This work presents the results obtained from comparing different tree depths in a Genetic Programming Algorithm to create agents that play the Planet Wars game. Three different maximum levels of the tree have been used (3, 7 and Unlimited) and two bots available in the literature, based on human expertise, and optimized by a Genetic Algorithm have been used for training and comparison. Results show that in average, the bots obtained using ourmethod equal or outperform the previous ones, being themaximumdepthof thetreearelevantparameterfor thealgorithm.
Cite
CITATION STYLE
García-Sánchez, P., Fernández-Ares, A., Mora, A. M., Castillo, P. A., González, J., & Guervós, J. J. M. (2014). Tree depth influence in genetic programming for generation of competitive agents for RTS games. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8602, pp. 411–421). Springer Verlag. https://doi.org/10.1007/978-3-662-45523-4_34
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.
