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Hey, that's awesome you've been trying to use some gradient-based learning for Raven! I wrote a bit more about how I used it in BeepBoop/Understanding BeepBoop. Is it similar to how you are doing things? It's tricky to apply deep learning methods to robocode due to compute/Java limitations, but it's definitely an interesting thing to explore!

Hi, it's in fact not so similar to what has been done with BeepBoop. It also is much simpler (and dumber) since I kind of rushed it :)

I'll actually add a small section named PyTorch to Raven's page explaining the current method I use to tune since it is rather hard to explain it in a single message and it would be easier to keep track of :)

Raven 3.58 was more of an experiment to see if APS would increase against the bots I tuned using rather than achieving general success. I agree that it is indeed very interesting to explore.

It also seems to me that Java might be getting SIMD support in the future(judging by the unstable Vector class in the latest version?) and quantization + SIMD could make a huge difference in execution speed of Neural Networks.