User talk:Xor

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Thread titleRepliesLast modified
Thoughts on entropy017:56, 1 June 2022
Manifold Learning217:20, 29 July 2021
Good to see robowiki is back!014:04, 12 June 2018

Thoughts on entropy

Targeting maximizes cross-entropy
Wave-surfing minimizes cross-entropy
Random movement maximizes self-entropy
But random movement doesn't minimize cross-entropy
Flattener minimizes "self" cross-entropy
But flattener doesn't maximize self-entropy

What deeper insight can you get from this?

Xor (talk)17:56, 1 June 2022

Manifold Learning

Guess Factor based methods generalize well, based on priori knowledge about robots moving in circles & max escape angle. Better methods such as precise max escape angle helps greatly. However given enough samples, I wonder whether some deep enough model can learn the shape of escape envelop, as well as precise max escape angle, etc. And generalize even better.

Xor (talk)13:25, 27 July 2021

I could imagine developing some sort of "LearnedFactor" function that takes as input the firing angle along with the enemy's position, velocity, maybe more complex features like precise MAE, etc. As long as the function is invertible with respect to the firing angle you could then do KNN with those instead of GuessFactors.

--Kev (talk)02:27, 28 July 2021

The biggest challenge will be how to deal with different settings in recorded and aiming. Guess Factor indeed do this with orbital movement assumption, and PIF with not moving out of wall.


I'm thinking about some end2end deep model, where transformations between recorded and aiming angles can be learnt automatically. E.g. Given a sequence of historical wave intersect location, movement and bullet hits, try to predict the next wave intersect location.

Xor (talk)17:07, 29 July 2021
 
 

Good to see robowiki is back!

Thanks Skilgannon and Voidious for maintaining the awesome robowiki and literumble!

I almost couldn’t wait to put my new bots into rumble ;)

Xor (talk)14:03, 12 June 2018