Difference between revisions of "Thread:Talk:Curve flattening/Shooting Curve Flatteners/reply (5)"
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There is a problem with this approach. Typically, you have about 10 sectors | There is a problem with this approach. Typically, you have about 10 sectors | ||
to shoot (if we divide guess factor range, by the bot body). Good curve flattener could be anywhere in a random fashion, even in just visited sector. | to shoot (if we divide guess factor range, by the bot body). Good curve flattener could be anywhere in a random fashion, even in just visited sector. | ||
| − | So at best you increased your chances to 1/9 vs 1/10, in practice it is still 1/10. I have a random gun among list of available ones | + | So at best you increased your chances to 1/9 vs 1/10, in practice it is still 1/10. I have a random gun among list of available ones for my bots, often it gives the best result against curve flatteners. Sometimes, antiguess factor would lead you in wrong direction: I think [[DrussGT]] avoids GF=0, but with negative weight for visited spots, you soon will fire at GF=0 only, and unavoidably lose. |
My strategy just fire randomly in this case, at least you get a chance to hit. | My strategy just fire randomly in this case, at least you get a chance to hit. | ||
Latest revision as of 02:49, 5 August 2017
There is a problem with this approach. Typically, you have about 10 sectors to shoot (if we divide guess factor range, by the bot body). Good curve flattener could be anywhere in a random fashion, even in just visited sector. So at best you increased your chances to 1/9 vs 1/10, in practice it is still 1/10. I have a random gun among list of available ones for my bots, often it gives the best result against curve flatteners. Sometimes, antiguess factor would lead you in wrong direction: I think DrussGT avoids GF=0, but with negative weight for visited spots, you soon will fire at GF=0 only, and unavoidably lose.
My strategy just fire randomly in this case, at least you get a chance to hit.
