Abstract
In this work, we show how Genetic Programming can be used to create game playing strategies for 2-AntWars, a deterministic turn-based two player game with local information. We evaluate the created strategies against fixed, human created strategies as well as in a coevolutionary setting, where both players evolve simultaneously. We show that genetic programming is able to create competent players which can beat the static playing strategies, sometimes even in a creative way. Both mutation and crossover are shown to be essential for creating superior game playing strategies.
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Inführ, J., Raidl, G.R. (2012). Automatic Generation of 2-AntWars Players with Genetic Programming. In: Moreno-Díaz, R., Pichler, F., Quesada-Arencibia, A. (eds) Computer Aided Systems Theory – EUROCAST 2011. EUROCAST 2011. Lecture Notes in Computer Science, vol 6927. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27549-4_32
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DOI: https://doi.org/10.1007/978-3-642-27549-4_32
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