Difference between revisions of "Mean Targeting"

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(Mean Targeting methods)
 
 
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A style of [[Targeting]] that averages the data from a few recent scans to use as input to its prediction algorithm.
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A style of [[targeting]] that averages the data from a few recent scans to use as input to its prediction algorithm.
  
 
== Linear Mean ==
 
== Linear Mean ==
  
Given the enemy's current position and their position <code>t</code> ticks in the past, assume the enemy will continue to move with the same direction and average speed deduced from these scans. The pseudo-code would look like this:
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Given the enemy's current position and their position <code>t</code> ticks in the past, assume the enemy will continue to move with the same direction and average speed deduced from these scans. The pseudocode would look like this:
 
* Take a present scan position and an older scan position, <code>t</code> ticks in the past.  Ignore actual heading and velocity.  
 
* Take a present scan position and an older scan position, <code>t</code> ticks in the past.  Ignore actual heading and velocity.  
 
* Find the angle from from the old scan to the new one. This is the mean heading.  
 
* Find the angle from from the old scan to the new one. This is the mean heading.  
 
* Find the distance between the two points and divide by <code>t</code>. This is the mean velocity.  
 
* Find the distance between the two points and divide by <code>t</code>. This is the mean velocity.  
* Use these values as input to a [[Linear Targeting]] algorithm.
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* Use these values as input to a [[linear targeting]] algorithm.
  
 
== Circular Mean ==
 
== Circular Mean ==
  
Given a collection of <code>x</code> recent scans of the enemy, calculate his average velocity and turn rate and assume that he will continue to move with those values. The pseudo-code would look like this:
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Given a collection of <code>x</code> recent scans of the enemy, calculate his average velocity and turn rate and assume that he will continue to move with those values. The pseudocode would look like this:
 
* Iterate over the group of scans, summing the <code>x - 1</code> heading changes and <code>x</code> velocities.  
 
* Iterate over the group of scans, summing the <code>x - 1</code> heading changes and <code>x</code> velocities.  
 
* Divide the sum of heading changes by <code>x - 1</code> to find the mean heading change.
 
* Divide the sum of heading changes by <code>x - 1</code> to find the mean heading change.
 
* Divide the sum of velocities by <code>x</code> to find the mean velocity.
 
* Divide the sum of velocities by <code>x</code> to find the mean velocity.
* Use these values as input to a [[Circular Targeting]] algorithm.
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* Use these values as input to a [[circular targeting]] algorithm.
  
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{{Targeting Navbox}}
 
[[Category:Simple Targeting Strategies]]
 
[[Category:Simple Targeting Strategies]]

Latest revision as of 19:18, 1 April 2011

A style of targeting that averages the data from a few recent scans to use as input to its prediction algorithm.

Linear Mean

Given the enemy's current position and their position t ticks in the past, assume the enemy will continue to move with the same direction and average speed deduced from these scans. The pseudocode would look like this:

  • Take a present scan position and an older scan position, t ticks in the past. Ignore actual heading and velocity.
  • Find the angle from from the old scan to the new one. This is the mean heading.
  • Find the distance between the two points and divide by t. This is the mean velocity.
  • Use these values as input to a linear targeting algorithm.

Circular Mean

Given a collection of x recent scans of the enemy, calculate his average velocity and turn rate and assume that he will continue to move with those values. The pseudocode would look like this:

  • Iterate over the group of scans, summing the x - 1 heading changes and x velocities.
  • Divide the sum of heading changes by x - 1 to find the mean heading change.
  • Divide the sum of velocities by x to find the mean velocity.
  • Use these values as input to a circular targeting algorithm.