Using previous GFs as dimensions

I'm curious how you're structuring this: Do you condense these 5 GFs into one attribute, or are they 5 independent attributes?

The most practical example this reminds me of is I believe Skilgannon uses his own last GF as an input to his gun to help crushing mirror movement. Using the enemy's previous movements I would guess to behave similarly to attributes like displacement distance last X ticks or time since velocity change.

My only other comments is that 5 seems like a lot. At an interval of 14 ticks, that's 70 ticks into the past, and more if you count the time it took to reach that first GF. My "distance last X" experiments have never gone past ~40 ticks, IIRC, and even that was not a strong signal.

19:07, 20 December 2013

Straw already said that there are six dimensions in his(?) gun, one for decay, and one for each of the enemy's last five visited GFs.

19:25, 20 December 2013

I'm just curious if they're being treated independently. A sequence like 0, 0.2, 0.4, 0.6, 0.8 actually might be quite close to 0.2, 0.4, 0.6, 0.8, 1.0, but if they're all treated independently, your classification won't see it that way.

19:30, 20 December 2013

If one wanted to make the ones you mention be treated similar, the way to do it would be to make the dimensions either:

`GF[i], (GF[i] - GF[i-1]), (GF[i-1] - GF[i-2]), (GF[i-2] - GF[i-3]), (GF[i-3] - GF[i-4])`

or perhaps:

`GF[i], (GF[i] - GF[i-1]), (GF[i] - GF[i-2]), (GF[i] - GF[i-3]), (GF[i] - GF[i-4])`

(where index 'i' is the most recent wave, 'i-1' is the second most recent wave, etc)

Of course, whether that would give better results than all independantly I have no idea about... and which of those ways of making it relative would be better I'm not sure about either.

19:49, 20 December 2013

I appreciate the concerned ? with his. I am male though.

21:04, 20 December 2013

Doesn't DrussGT use the opponents last GF in his targeting system, not his own? (in addition, a dimension called my expected mirror rotation at bullet hit time) It looks so far into the past because in both surfers and flatteners, (especially surfers) recent past movements are a good indicator of present movements. Fast decaying "normal" anti surfer guns do a similar thing in a different way.

21:02, 20 December 2013

Yes I do something similar in DrussGT, in two places.

1. I use the enemy's current GF as a gun attribute to help with oscillators

2. I use my predicted GF one BFT in the future as in input to help against mirror bots (and it helps a little against most other bots as well)

I'm also curious about the last 5 GFs - are they sorted and fed to the gun in ascending order, or are they used in the order they were collected? I feel that some distance/clustering method other than KNN might work best in this situation.

21:11, 20 December 2013

I agree that something other than KNN might be better, but its what I have set up right now. No sorting happens, the gun just has a dimension for the last GF, a dimension for the GF before that, etc. I found increased performance dropping data decay, going to 10 past GFs, and using descending weights on older GFs. Data decay shouldn't be necessary with this setup as if the opponent changes their movement patterns, they will change their GF sequences.

04:18, 21 December 2013

Exiting anti flattener results! The gun gets pretty much the same hitrate vs DrussGT (which can't shoot) with DrussGTs flattener allowed to turn on or forced off. Around 10.6% weighted from DrussGT's console. For comparison, Diamond's gun gets around 12.6%. The interesting thing is that the hitrate didn't go down at all with the flattener.

04:42, 21 December 2013

When I increase K in my GFs as dimensions gun, performance improves. Interesting.

23:03, 22 December 2013

by exactly how much per k

00:00, 23 December 2013

Why don't you test?

01:03, 23 December 2013