Pei, You are right, that does sound better than "quick-and-dirty". And more relevant, because my primary interest here is to get a handle on what normative epistemology should tell us to conclude if we do not have time to calculate the full set of consequences to (uncertain) facts.
It is unfortunate that I had to use biased language, but probability is of course what I am familiar with... I suppose, though, that most of the terms could be roughly translated into NARS? Especially independence, and I should hope conditional independence as well. Collapsing probabilities can be restated as generally collapsing uncertainty. Thanks for the links. The reason for singling out these three, of course, is that they have already been discussed on this list. If anybody wants to point out any others in particular, that would be great. --Abram On Wed, Sep 17, 2008 at 3:54 PM, Pei Wang <[EMAIL PROTECTED]> wrote: > On Wed, Sep 17, 2008 at 1:46 PM, Abram Demski <[EMAIL PROTECTED]> wrote: >> 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 > > Yes, I heard of this guy a few times, who happens to use the same name > for his project as mine. ;-) > >> Here is my list: >> >> 1. Well-defined uncertainty semantics (either probability theory or a >> well-argued alternative) > > Agree, and I'm glad that you mentioned this item first. > >> 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 > > As you admitted in the following, the language is biased. Using > theory-neutral language, I'd say the requirement is "to derive > conclusions with available knowledge and resources only", which sounds > much better than "quick-and-dirty" to me. > >> 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 > > As soon as you don't assume there is a "model", this item and the > above one become similar, which are what I called "revision" and > "inference", respectively, in > http://www.cogsci.indiana.edu/pub/wang.uncertainties.ps > >> 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? > > If you consider approaches with various scope and maturity, there are > much more than these three approaches, and I'm sure most of people > working on them will claim that they are also "general purpose". > Interested people may want to browse http://www.auai.org/ and > http://www.elsevier.com/wps/find/journaldescription.cws_home/505787/description#description > > Pei > > > ------------------------------------------- > 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/?&; > Powered by Listbox: http://www.listbox.com > ------------------------------------------- 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
