Abstract
This work describes an evolutionary algorithm (EA) for evolving the constants, weights and probabilities of a rule-based decision engine of a bot designed to play the Planet Wars game. The evaluation of the individuals is based on the result of some non-deterministic combats, whose outcome depends on random draws as well as the enemy action, and is thus noisy. This noisy fitness is addressed in the EA and then, its effects are deeply analysed in the experimental section. The conclusions shows that reducing randomness via repeated combats and re-evaluations reduces the effect of the noisy fitness, making then the EA an effective approach for solving the problem.
This work has been supported in part by project P07-TIC-03044, awarded by the Andalusian Regional Government.
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Mora, A.M., Fernández-Ares, A., Merelo-Guervós, JJ., García-Sánchez, P. (2012). Dealing with Noisy Fitness in the Design of a RTS Game Bot. In: Di Chio, C., et al. Applications of Evolutionary Computation. EvoApplications 2012. Lecture Notes in Computer Science, vol 7248. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29178-4_24
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DOI: https://doi.org/10.1007/978-3-642-29178-4_24
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