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Hey, congrats on the great update!
From what I understand from your version history message, what you did in this version is a simpler version of what I have been working on for a while now - the idea of gunheat waves in melee. I'll release tomorrow hopefully, but in the mean time some of the infrastructure I needed in order to get there enabled me to do some other things which are interesting - mostly around bullet power management.
And thanks for the competition, it is difficult to find motivation without strong opponents! In fact, thanks to all the robocoders who have been recently active, I was afraid that the robocode community had died! It is great seeing some new life in the rumble, especially with very strong bots!
Thanks! I haven't looked into the concept of gun heat waves that much yet, but it's interesting, especially in melee where it's a bigger challenge to detect enemy waves.
What I changed in 1.10 is actually concerning the gun. Firestarter fires a virtual bullet wave each tick now. Apparently this speeds up learning and it increased the performance of the guess factor gun, even against surfers.
I am curious about your new version! And I agree, I am happy to see so many people active, and I wonder where this activity suddenly comes from. Maybe AI and Deep Learning becoming popular in the media also sparked new interest in Robocode.
Ah, ok. I thought it would be movement related, and perhps you are doing some kind of shrapnel dodging.
A good way I found to get a balance between the every-tick vs fire-only is to use "time to/from fire" as an attribute, this way you get the fast learning as well as the better targeting of bots that react to enemy fire once you have enough data.
As far as I understood, shrapnel surfing is about simulating virtual bullets and moving away from them by using anti gravity. I tried something like this in earlier versions, but I couldn't make it work that well. Next, I used pure minimum risk movement which worked well. Currently, it is a mix of both positional and wave evaluation.
Thank you, good to know about that time attribute :)