Using previous GFs as dimensions
The highlighted comment was edited in this revision. [diff]
I tried making a gun which uses kNN classification, in which the one dimension is shots (for data decay) and the others are the last 5 GFs the opponent went to on firing waves. Its very simple right now and I haven't tried much, but it does reasonably well (as in it doesn't get crushed, does better than random targeting) vs both surfers and simple movers. (Haven't tried against random movement yet) It seems similar to pattern matching on the opponents GFs. Any ideas?
Interesting. I think you should definitely test against RM, because surfers generally don't like anything with bullet waves, and simple movers are pretty easy to hit. Also, you might want to start with the basics (distance, velocity, relative heading, acceleration...) before you get into data decay and experimental dimensions. Good luck.
Don't worry! I am actively optimizing my more "normal" gun using standard predictors. What bots would you recommend as good test bots with strong RM? Tmservo its just a 6 dimensional KNN, 5 are lastGFs normalized to 0-1, last one is sqrt(shots)* .5. I haven't added any kernel density stuff to this tree, I plan to try that.
