Imitation is a powerful and pervasive primitive underlying examples of intelligent behavior 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^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 behavior. 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.

[Though this chapter was published later, an earlier paper describes how this bot was improved for later competitions: paper]

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In Philip F. Hingston, editors, Believable Bots, 151--170, 2012. Springer Berlin Heidelberg.

@inbook{karpov:believablebots12, title={Believable Bot Navigation via Playback of Human Traces}, author={Igor V. Karpov and Jacob Schrum and Risto Miikkulainen}, booktitle={Believable Bots}, editor={Philip F. Hingston}, publisher={Springer Berlin Heidelberg}, pages={151--170}, url="http://nn.cs.utexas.edu/?karpov:believablebots12", year={2012} }