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. ~PMFrom: [email protected] To: [email protected] Subject: RE: [agi] Numeric Similarity Date: Fri, 21 Feb 2014 06:02:46 -0800Thanks 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 AGI | Archives | Modify Your SubscriptionAGI | Archives | Modify Your Subscription AGI | Archives | Modify Your Subscription ------------------------------------------- AGI Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/21088071-f452e424 Modify Your Subscription: https://www.listbox.com/member/?member_id=21088071&id_secret=21088071-58d57657 Powered by Listbox: http://www.listbox.com
