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They actually did, one of the approaches they tested included holding down combinations of keys for variable durations (the "Representation 4: Bitmask-Duration Sequence"), however they didn't get any viable runners using that approach. Their conclusion was that with the constraints they were operating under (ie. only 1,000 fitness evaluations etc), the solution space was too broad for that approach to find any viable strategies. Main takeaway for me was that this form of genetic algorithm works best & converges most quickly the simpler you can make the search space.



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