Reproducing the Results

Fragment of a discussion from Talk:WhiteFang
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:I have just wondered how you normalize dangers in ScalarBot or since it's not OS what is the general way of doing it? In the latest version of [[WhiteFang]] I use
<pre>
weight * MaximumPossibleDistance / (euclidean_distance + 1) / predictionNum
</pre>
to have a balance between different weighting schemes and K's.

Return to Thread:Talk:WhiteFang/Reproducing the Results/reply (4).

Just have a look at DrussGT and Diamond, ScalarBot uses similar formula. And most (new) bots imitate this style as well.

Make sure to use bullet damage and time-till-hit for weighting one wave vs another. Depending on the type of enemy this can make a big difference.

Skilgannon (talk)‎

Thank you for your response. The weighting system I wrote above only affects the bins. Later I divide/multiply those values while choosing the best movement option since WhiteFang has a bin-based KNN Algorithm(The code base was originally designed for Neural Networks).

Actually, I have a logical mistake in my movement but I didn't fix it yet since I wanted a controlled testing environment.

Dsekercioglu (talk)‎

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