Automatic Generation of 2-AntWars Players with Genetic Programming
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.
KeywordsAutomatic Strategy Creation Strongly Typed Genetic Programming Game Rule Evaluation
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