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Extracting NPC behavior from computer games using computer vision and machine learning techniques

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3 Author(s)
Fink, A. ; Dept. of Math., California Univ., Berkeley, CA ; Denzinger, J. ; Aycock, J.

We present a first application of a general approach to learn the behavior of NPCs (and other entities) in a game from observing just the graphical output of the game during game play. This allows some understanding of what a human player might be able to learn during game play. The approach uses object tracking and situation-action pairs with the nearest-neighbor rule. For the game of Pong, we were able to predict the correct behavior of the computer controlled components approximately 9 out of 10 times, even if we keep the usage of knowledge about the game (beyond observing the images) at a minimum

Published in:

Computational Intelligence and Games, 2007. CIG 2007. IEEE Symposium on

Date of Conference:

1-5 April 2007