K() would be the Kolmogorov complexity. Matt Mahoney always complains
that the K Complexity is not computable but never talks about it being
estimable.
John
On 2014-02-21 19:05, Piaget Modeler wrote:
I like this too. How would one define K ?
~PM
-------------------------
From: [email protected]
To: [email protected]
Subject: RE: [agi] Numeric Similarity
Date: Fri, 21 Feb 2014 16:18:16 -0500
It could also be something like this:
Similarity(A, B) = 1 / (1 + |K’(A) – K’(B)|)
where K’(A) is the estimated complexity of A. The K’ function is
dependent on observer formulaics and resources.
John
FROM: Piaget Modeler [mailto:[email protected]]
SENT: Friday, February 21, 2014 3:46 PM
TO: AGI
SUBJECT: RE: [agi] Numeric Similarity
Actually Aaron Hosford just recommended
1 / (1 + | a - b | )
Which I like much better.
Thanks Aaron.
~PM
-------------------------
From: [email protected]
To: [email protected]
Subject: RE: [agi] Numeric Similarity
Date: Fri, 21 Feb 2014 06:02:46 -0800
Thanks to all respondents.
In the end I found a classic numeric similarity metric: 1 - | a - b |
It's not ideal since numeric scores can dominate other attribute
scores.
Ergo, I have to devise a good weighting scheme.
Nothing's perfect I suppose.
Cheers,
~ PM
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