Tree depth influence in Genetic Programming for generation of competitive agents for RTS games

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by Pablo García-Sánchez, Antonio Fernández-Ares, Antonio Miguel Mora, Pedro Ángel Castillo, Juan Julián Merelo, Jesús González
in EvoAPPS posters

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.

More info is available at the OSGiLiath Evolutionary Framework webpage.

1 comentario en “Tree depth influence in Genetic Programming for generation of competitive agents for RTS games”

  1. Pingback: This was a triumph: Evolving intelligent bots for videogames. And for Science. | GeNeura Team

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