Abstract
Imitation is a powerful and pervasive primitive underlying examples of intelligent behaviour in nature. Can we use it as a tool to help build artificial agents that behave like humans do? This question is studied in the context of the BotPrize competition, a Turing-like test where computer game bots compete by attempting to fool human judges into thinking they are just another human player. One problem faced by such bots is that of human-like navigation within the virtual world. This chapter describes the Human Trace Controller, a component of the \({UT{\char 94}2}\) bot which took second place in the BotPrize 2010 competition. The controller uses a database of recorded human games in order to quickly retrieve and play back relevant segments of human navigation behaviour. Empirical evidence suggests that the method of direct imitation allows the bot to effectively solve several navigation problems while moving in a human-like fashion.
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Acknowledgments
The authors would like to thank Philip Hingston for organizing the BotPrize competitions and 2K Australia for sponsoring it. The authors would also like to thank students in the Freshman Research Initiative’s Computational Intelligence in Game Design stream and members of the Neural Networks Research Group at the University of Texas and to Christopher Tanguay and Peter Djeu for participating in recordings of human game traces and for volunteering to critique and evaluate versions of \({UT{\char 94}2}\) . This research was supported in part by the NSF under grants DBI-0939454 and IIS-0915038 and by the Texas Higher Education Coordinating Board grant 003658-0036-2007.
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Karpov, I.V., Schrum, J., Miikkulainen, R. (2013). Believable Bot Navigation via Playback of Human Traces. In: Hingston, P. (eds) Believable Bots. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32323-2_6
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DOI: https://doi.org/10.1007/978-3-642-32323-2_6
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