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Game Designers Training First Person Shooter Bots
Michelle McPartland and Marcus Gallagher
University of Queensland, Australiamichelle@itee.uq.edu.au
marcusg@itee.uq.edu.au
Abstract. Interactive training is well suited to computer games as it allows game designers to interact with otherwise autonomous learning algorithms. This paper investigates the outcome of a group of five commercial first person shooter game designers using a custom built interactive training tool to train first person shooter bots. The designers are asked to train a bot using the tool, and then comment on their experiences. The five trained bots are then pitted against each other in a deathmatch scenario. The results show that the training tool has potential to be used in a commercial environment.
Keywords: Reinforcement learning, interactive training, first person shooters, game artificial intelligence
LNAI 7691, p. 397 ff.
lncs@springer.com
© Springer-Verlag Berlin Heidelberg 2012