Hi everyone, Most people on this list should know about at least 3 uncertain logics claiming to be AGI-grade (or close):
--Pie Wang's NARS --Ben Goertzel's PLN --YKY's recent hybrid logic proposal It seems worthwhile to stop and take a look at what criteria such logics should be judged by. So, I'm wondering: what features would people on this list like to see? Here is my list: 1. Well-defined uncertainty semantics (either probability theory or a well-argued alternative) 2. Good at quick-and-dirty reasoning when needed --a. Makes unwarranted independence assumptions --b. Collapses probability distributions down to the most probable item when necessary for fast reasoning --c. Uses the maximum entropy distribution when it doesn't have time to calculate the true distribution --d. Learns simple conditional models (like 1st-order markov models) for use later when full models are too complicated to quickly use 3. Capable of "repairing" initial conclusions based on the bad models through further reasoning --a. Should have a good way of representing the special sort of uncertainty that results from the methods above --b. Should have a "repair" algorithm based on that higher-order uncertainty The 3 logics mentioned above vary in how well they address these issues, of course, but they are all essentially descended from NARS. My impression is that as a result they are strong in (2a) and (3b) at least, but I am not sure about the rest. (Of course, it is hard to evaluate NARS on most of the points in #2 since I stated them in the language of probability theory. And, opinions will differ on (1).) Anyone else have lists? Or thoughts? --Abram ------------------------------------------- agi Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/ Modify Your Subscription: https://www.listbox.com/member/?member_id=8660244&id_secret=114414975-3c8e69 Powered by Listbox: http://www.listbox.com
