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Yes, exactly! To do multiple choice, it samples the next tick at (weighted) random rather than picking the most frequent one as in classic single tick. Definitely using more input features could help, but I think velocity/deltaHeading/acceleration are the most important features and the play-it-forward sort of implicitly captures wall features by rejecting movement trajectories that go out of bounds.