Difference between revisions of "Category:Advanced Targeting Strategies"

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m (New page: "Advanced targeting" strategies are those that use sophisticated data collection and statistical analysis in their targeting algorithms. There are a wide range of algorithms that fit this ...)
 
m (re-specify as any learning gun, maybe rename later)
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"Advanced targeting" strategies are those that use sophisticated data collection and statistical analysis in their targeting algorithms. There are a wide range of algorithms that fit this category, but most include one or more of the following:  
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Targeting strategies that collect data and learn how an enemy moves. There are a wide range of algorithms that fit this category, but most include one or more of the following:  
  
* [[Waves]], a system for collection of [[GuessFactors]] or [[Bearing Offsets]] that hit the enemy.
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* [[Waves]], a system for collection of [[GuessFactor]]s or [[Bearing Offsets]] that hit the enemy.
* [[PatternMatching]], a system that logs individual enemy movements, frame by frame, for analysis of past movements and projection of future movements.
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* [[Pattern Matching]], a system that logs individual enemy movements, frame by frame, for analysis of past movements and projection of future movements.
* [[StateMatching]], where the current situation is compared to a log of many or all past situations to use as reference for the current situation.
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* [[Dynamic Clustering]], where the current situation is compared to a log of many or all past situations to use as reference for the current situation.
  
 
[[Category:Targeting|Advanced Targeting Strategies]]
 
[[Category:Targeting|Advanced Targeting Strategies]]

Revision as of 20:12, 8 September 2011

Targeting strategies that collect data and learn how an enemy moves. There are a wide range of algorithms that fit this category, but most include one or more of the following:

  • Waves, a system for collection of GuessFactors or Bearing Offsets that hit the enemy.
  • Pattern Matching, a system that logs individual enemy movements, frame by frame, for analysis of past movements and projection of future movements.
  • Dynamic Clustering, where the current situation is compared to a log of many or all past situations to use as reference for the current situation.