Did the flattener help against weak bots?

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Revision as of 29 November 2012 at 16:02.
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Did the flattener help against weak bots?

So, the best version that i ever had was 1.95, by a fairly large margin. In 1.96, I fixed a bug where I had accidentally had the flattener on for any bot hitting me more than (normalizedProbability-0.045) which happens with way more bots than a flattener would usually be used for (it corresponds to roughly a 7% hit rate). Is it possible that the flattener helps?

    AW02:47, 9 November 2012

    I think there's only one way to find out. :-) Try lowering the threshold?

    But I'd say it largely depends on how heavily your flattener is weighted, how your hit percentage is normalized, and so on. A 7% hit rate might be low but it really depends on the distance and bullet power, so I'd have to see how you're normalizing it to say.

    Diamond's main flattener is enabled at hit rate = 5.9%, normalized to precise escape angle = 0.98 and precise bot width of 0.1 radians, which is something like bullet power = 2 and distance = 500. I also found a little bit of improvement with another lower weighted flattener enabled at half that hit percentage. So maybe that can give you a ballpark idea of how high/low your threshold is compared to mine, which I think is pretty well tuned. I also add a margin of error based on number of shots, like they use to calculate margin of error in election polling, which lets me set it as low as possible without much risk. (So it's only really 5.9 after a lot of shots, early on it's quite a bit higher.)

      Voidious03:39, 9 November 2012
       

      Another thought is don't be afraid to just re-release 1.95 as 1.95b. There could have been some weird battles or something and you are just chasing shadows - I've definitely had that happen.

        Voidious17:07, 13 November 2012
         

        Well, the re-release is showing that 1.95 really was the strongest by a large margin. When I said I had the flattener on, I was actually being imprecise, what I had was one of my "semi-advanced" classifiers being trained with visits and hits and one of my flatteners being trained with only hits. Regardless, I ran some tests this morning that show 1.99.5's gun as being weaker than 1.95. I had previously spent all my time searching for something i broke in the movement when I "fixed" the gun, but I guess I broke something in the gun instead...

        My changes to the gun (from Gilgalad's targeting strategy page): Version 1.99.4 is, I think, the first robot to handle virtual waves exactly. After a real wave is fired, the virtuality and bullet power attributes for the real waves are set. Bullet power is a weighted average of the two real waves around the virtual waves (in terms of time). At training time, the waves play through a log of positions with the new bullet power. Attributes, which can depend on bullet power, are calculated only when training and aiming (aiming uses the estimated bullet power).

        That should only improve the accuracy if done correctly, right?

          AW17:02, 29 November 2012