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 our method equal or outperform the previous ones, being the maximum depth of the tree a relevant parameter for the algorithm.
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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: Esparcia-Alcázar, A., Mora, A. (eds) Applications of Evolutionary Computation. EvoApplications 2014. Lecture Notes in Computer Science(), vol 8602. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-45523-4_34
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DOI: https://doi.org/10.1007/978-3-662-45523-4_34
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