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Awesome enty | 23 | 18:57, 23 June 2021 |
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This new bot of yours really is awesome ! It is really beating the hell out of the topbots, even without BulletShielding.
Alas I am not able to run any battles for it, as I am still on Java 8.
alas, in version 0.11, still some parts are not Java 8 compatible: kc/mega/game/Battleffield has been compiled by version 57.0.
Does not matter that much, I am just not able (currently) to run any battles for it. Same for Raven as it has been compiled by version 55.0.
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Return to Thread:Talk:BeepBoop/Awesome enty/reply (4).
I've downloaded Java 13, I can now run battles for BeepBoop. After rebuilding the robot-database, also Raven and WaveShark run fine. Note that for my development I will still use the compiler option '-source 1.8'
Oh wow, missed this! Awesome work Kev, you have a history of popping up with surprise entries =)
I'd be curious to know more about the Tensorflow work you did to make the KNN features...
Thanks! I wrote a brief description under BeepBoop/Understanding_BeepBoop, but I'll release the code too once I get it cleaned up.
Aha, I missed the last section. Surprised there wasn't more to gain from some kind of deeper embedding model.
Me too, and I'll maybe revisit it at some point. Theoretically a deeper embedding model could learn feature interactions like "wall-ahead is more important when velocity is 8 than when it is 0"
I’m surprised as well. Btw, how many layers are you using in the deeper model? And is that fully connected? I guess some deeper models with explicit feature interactions may work better in robocode scenario, given high noise. I would try things like Deep&Cross, DeepFM, etc.
It's possible that the KNN already takes that into account sufficiently. Maybe if you bump the cluster size up a lot, and change the kernel width for cluster weighting, it might force this part of the learning into the NN instead?
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