Abstract: Next-generation immersive virtual environments and video games will require virtual agents with human-like visual attention and gaze behaviors. A critical step is to devise efficient visual processing heuristics to select locations that would attract human gaze in complex dynamic environments. One promising approach to designing such heuristics draws on ideas from computational neuroscience. We compared several such heuristics with eye movement recordings from five observers playing video games, and found that heuristics which detect outliers from the global distribution of visual features were better predictors of human gaze than were purely local heuristics. Heuristics sensitive to dynamic events performed best overall. Further, heuristic prediction power differed more between games than between different human observers. Our findings suggest simple neurally-inspired algorithmic methods to predict where humans look while playing video games.