AW: typo

2012-02-09T15:44:46Z

typo

AW: Reply to Precise MEA

2012-02-09T15:43:48Z

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Well, that depends on how you use precise MEA. For Gilgalad I was scaling bin size by the MEA So I think that the buggy / random MEA added noise to the GF's. Another interesting point is that moving ahead 0.5 GF and then back 0.5 GF won't always end at zero because the wall smoothing may make the 0.5 GF much closer to GF zero than -0.5 is. However, that is a problem no matter what kind how you calculate your GF's. I haven't given it detailed thought, but I think that as long as the enemy is making enough random and independent movement decisions between when you fire and when the wave breaks, the [[http://en.wikipedia.org/wiki/Central_limit_theorem centeral limit theorem]] proves that their movement porfile will still approximate the normal distribution (which is why I think bin smoothing makes sense). However, I am unsure whether having the GF's scale or not would allow better/faster learning.

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−	Well, that depends on how you use precise MEA. For Gilgalad I was scaling bin size by the MEA So I think that the buggy / random MEA added noise to the GF's. Another interesting point is that moving ahead 0.5 GF and then back 0.5 GF won't always end at zero because the wall smoothing may make the 0.5 GF much closer to GF zero than -0.5 is. However, that is a problem no matter ~~what kind~~ how you calculate your GF's. I haven't given it detailed thought, but I think that as long as the enemy is making enough random and independent movement decisions between when you fire and when the wave breaks, the [[http://en.wikipedia.org/wiki/Central_limit_theorem centeral limit theorem]] proves that their movement porfile will still approximate the normal distribution (which is why I think bin smoothing makes sense). However, I am unsure whether having the GF's scale or not would allow better/faster learning.	+	Well, that depends on how you use precise MEA. For Gilgalad I was scaling bin size by the MEA So I think that the buggy / random MEA added noise to the GF's. Another interesting point is that moving ahead 0.5 GF and then back 0.5 GF won't always end at zero because the wall smoothing may make the 0.5 GF much closer to GF zero than -0.5 is. However, that is a problem no matter how you calculate your GF's. I haven't given it detailed thought, but I think that as long as the enemy is making enough random and independent movement decisions between when you fire and when the wave breaks, the [[http://en.wikipedia.org/wiki/Central_limit_theorem centeral limit theorem]] proves that their movement porfile will still approximate the normal distribution (which is why I think bin smoothing makes sense). However, I am unsure whether having the GF's scale or not would allow better/faster learning.

Thread:Talk:Gilgalad/targetingStrategy/Precise MEA/reply (3) - Revision history

AW: typo

AW: Reply to Precise MEA