> Beside the problem you mentioned, there are other issues. Let me start > at the basic ones: > > (1) In probability theory, an event E has a constant probability P(E) > (which can be unknown). Given the assumption of insufficient knowledge > and resources, in NARS P(A-->B) would change over time, when more and > more evidence is taken into account. This process cannot be treated as > conditioning, because, among other things, the system can neither > explicitly list all evidence as condition, nor update the probability > of all statements in the system for each piece of new evidence (so as > to treat all background knowledge as a default condition). > Consequently, at any moment P(A-->B) and P(B-->C) may be based on > different, though unspecified, data, so it is invalid to use them in a > rule to calculate the "probability" of A-->C --- probability theory > does not allow cross-distribution probability calculation. > > (2) For the same reason, in NARS a statement might get different > "probability" attached, when derived from different evidence. > Probability theory does not have a general rule to handle > inconsistency within a probability distribution.
Of course, these issues can be handled in probability theory via introducing higher-order probabilities ... ben ------------------------------------------- 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
