Difference between revisions of "Thread:Talk:ScalarBot/Version History/WaveSurfing rethink"

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m (New thread: WaveSurfing rethink)
 
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Besides firing situations, when you are sure about that they are very likely to fire bullets they’ve fired before, downgrading to traditional wave surfing seems good. And for else, why risk dodging somewhere they aren’t firing at? If their targeting looks quite random (at given firing situation), sitting still or moving randomly are also good choices. And you won’t risk hitting the wall or get yourself stuck somewhere as well if you don’t move at all.  
 
Besides firing situations, when you are sure about that they are very likely to fire bullets they’ve fired before, downgrading to traditional wave surfing seems good. And for else, why risk dodging somewhere they aren’t firing at? If their targeting looks quite random (at given firing situation), sitting still or moving randomly are also good choices. And you won’t risk hitting the wall or get yourself stuck somewhere as well if you don’t move at all.  
  
For every bit of the future you can predict, you can always know what you can do better. A lot of bots are too strict, imo, following the design (and the assumptions behind) strictly. But I think we can do better, give more freedom to the bot itself (who always knows itself better), rather than planning everything in advance. Given the success in GF targeting and then kNN, I’m pretty sure there are still a lot to explore even in today, and there are still a lot for bots to improve.
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For every bit of the future you can predict, you can always know what you can do better. A lot of bots are too strict, imo, following the design (and the assumptions behind) strictly. But I think we can do better, give more freedom to the bot itself (who always knows the situation better), rather than planning everything in advance. Given the success in GF targeting and then kNN, I’m pretty sure there are still a lot to explore even in today, and there are still a lot for bots to improve.

Revision as of 15:11, 15 October 2017

Even though I have a bot that used to rank relatively high in the 1v1 division, I couldn’t think of myself fully understanding what I was doing and why it works. I was always assuming some GF targeting which fires at the most frequently visited gf, with the most popular attributes in mind. (e.g. segmenting on lateral velocity, accel, wall distance, etc. ).

And even though I tried to consider more types of enemy targeting strategies after that, I was still assuming some specific targeting strategy.

But today, after thinking about that in dreams, an idea just came up.

Can we just don’t assume anything about enemy strategy? Be tough yourself, and they’ll automagically have some trouble hitting you.

But that’s not enough for a top movement. Besides not showing weakness in all senses, it’ll be pity if you lose the chance to be better dodging them.

Statistics will always tell you the truth — once you are sure that they always fire head-on in some situations, why don’t you try your best to make them see the same situation again when aiming? Yes, I’m talking about automagical stop&go, but in my observation far more guns have similar weakness.

Besides firing situations, when you are sure about that they are very likely to fire bullets they’ve fired before, downgrading to traditional wave surfing seems good. And for else, why risk dodging somewhere they aren’t firing at? If their targeting looks quite random (at given firing situation), sitting still or moving randomly are also good choices. And you won’t risk hitting the wall or get yourself stuck somewhere as well if you don’t move at all.

For every bit of the future you can predict, you can always know what you can do better. A lot of bots are too strict, imo, following the design (and the assumptions behind) strictly. But I think we can do better, give more freedom to the bot itself (who always knows the situation better), rather than planning everything in advance. Given the success in GF targeting and then kNN, I’m pretty sure there are still a lot to explore even in today, and there are still a lot for bots to improve.