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 AGI | <https://www.listbox.com/member/archive/303/=now> Archives <https://www.listbox.com/member/archive/rss/303/19999924-4a978ccc> | <https://www.listbox.com/member/?&;> Modify Your Subscription <http://www.listbox.com> AGI | <https://www.listbox.com/member/archive/303/=now> Archives <https://www.listbox.com/member/archive/rss/303/248029-3b178a58> | <https://www.listbox.com/member/?&;> Modify Your Subscription <http://www.listbox.com> ------------------------------------------- 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
