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For movement, often a single bot is enough to prove a theory. Escape angle tuning is a rambot plus DevilFish, surfing mechanics is DoctorBob, anti-GF RaikoMicro, anti-fast-learning is Ascendant and for general unpredictability Shadow or Diamond. | For movement, often a single bot is enough to prove a theory. Escape angle tuning is a rambot plus DevilFish, surfing mechanics is DoctorBob, anti-GF RaikoMicro, anti-fast-learning is Ascendant and for general unpredictability Shadow or Diamond. | ||
− | Targeting I always find less interesting. Maybe because it is a more pure ML problem, with less ways to optimise that haven't already been | + | Targeting I always find less interesting. Maybe because it is a more pure ML problem, with less ways to optimise that haven't already been studied in a related field. I decided to brute-force it by adding lots of features and then using a genetic optimization to tune the weights against recordings of the entire rumble population, about 5000 battles. The surfers I did separately, but with the same process. |
Latest revision as of 23:15, 27 September 2017
It depends what I am working in.
For movement, often a single bot is enough to prove a theory. Escape angle tuning is a rambot plus DevilFish, surfing mechanics is DoctorBob, anti-GF RaikoMicro, anti-fast-learning is Ascendant and for general unpredictability Shadow or Diamond.
Targeting I always find less interesting. Maybe because it is a more pure ML problem, with less ways to optimise that haven't already been studied in a related field. I decided to brute-force it by adding lots of features and then using a genetic optimization to tune the weights against recordings of the entire rumble population, about 5000 battles. The surfers I did separately, but with the same process.