Difference between revisions of "Category:Statistical Targeting"

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(making Statistical Targeting a category)
 
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A family of [[targeting]] strategies that learn about the enemy's movement through the accumulation of relevant statistics. In particular, these methods tend to process input on the fly, updating an internal data structure from which they can quickly generate a firing angle in future situations; this is in contrast to [[Log Target|log-based targeting]] methods that store raw data and analyze it at fire time.
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A family of [[targeting]] strategies that learn about the enemy's movement through the accumulation of relevant statistics. In particular, these methods tend to process input on the fly, updating an internal data structure from which they can quickly generate a firing angle in future situations; this is in contrast to [[log-based targeting]] methods that store raw data and analyze it at fire time.
  
The statistics gathered could be anything that can be used to reconstruct a firing angle, such as the success rates of different [[:Category:Simple Targeting Strategies|simple targeters]] in a [[Virtual Guns]] array, the last [[Bearing Offset|bearing offset]] that would have hit the enemy, or a [[Segmentation|segmented]] array of [[Visit Count Stats]].
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The statistics gathered could be anything that can be used to reconstruct a firing angle, such as the success rates of different [[:Category:Simple Targeting Strategies|simple targeters]] in a [[Virtual Guns]] array, the last [[Bearing Offset|bearing offset]] that would have hit the enemy, or a [[Segmentation|segmented]] [[Visit Count Stats]] array of enemy [[GuessFactors]].
  
 
== See also ==
 
== See also ==
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* [[Waves]]
 
* [[Waves]]
  
[[Category:Advanced Targeting Strategies]]
 
 
[[Category:Targeting]]
 
[[Category:Targeting]]
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[[Category:Statistical Algorithms]]

Latest revision as of 15:29, 4 December 2012

A family of targeting strategies that learn about the enemy's movement through the accumulation of relevant statistics. In particular, these methods tend to process input on the fly, updating an internal data structure from which they can quickly generate a firing angle in future situations; this is in contrast to log-based targeting methods that store raw data and analyze it at fire time.

The statistics gathered could be anything that can be used to reconstruct a firing angle, such as the success rates of different simple targeters in a Virtual Guns array, the last bearing offset that would have hit the enemy, or a segmented Visit Count Stats array of enemy GuessFactors.

See also

Pages in category "Statistical Targeting"

The following 5 pages are in this category, out of 5 total.