> > One thing that complicates the problem is that ,in some cases, as well as > inferring probabilities one hasn't been given, one may want to make > corrections to probabilities one HAS been given. For instance, sometimes > one may be given inconsistent information, and one has to choose which > information to accept. > > For example, if you're told > > P(male) = .5 > P(young|male) = .4 > P(young) = .1 > > then something's gotta give, because the first two probabilities imply > P(young) >= .5*.4 = .2 > > Novamente's probabilistic reasoning system handles this problem pretty well, > but one thing we're struggling with now is keeping this "correction of > errors in the premises" under control. If you let the system revise its > premises to correct errors (a necessity in an AGI context), then it can > easily get carried away in cycles of revising premises based on conclusions, > then revising conclusions based on the new premises, and so on in a chaotic > trajectory leading to meaningless inferred probabilities. > > As I said before, this is a very simple incarnation of a problem that takes > a lot of other forms, more complex but posing the same essential challenge. > > -- Ben G
The first thing occurs to me (and probably has to you) as a solution to this dilemna is to use truth(confidence) values to set cut-off points for correction of contradictions. If P1 and P2 are contradictory, compare the truth values of the assertions. If they are very similar, do nothing, because it's impossible to know which is correct. If they vary significantly(and at least one of them is above a certain threshold), alter the probabilities towards one another, with respect to their relative truth. So if P1 has truth .95 and P2 has truth .2, adjust P1 slightly in the direction to relieve the contradiction. Adjust P2 greatly. Then, decrement the truth values of both of them using some nonlinear function. High truth assertions should probably be "sticky", in that it they decrease very slowly, so that you need a great number of contradictory low-truth contradictions to bring a single high-truth value down to mid-range truth values. By decreasing the energy in the truth table with each sweep, and only effecting changes as long as truth values are above a cut-off threshold, you are guaranteed to reach a state of equilibrium eventually. However, the system I've described can end up with a stable state of many mutually contradictory statements of similar truth values. These states would need to be resolved by another system, perhaps one that creates goal nodes to address contradictions through the acquisition of new information. -Brad ------- To unsubscribe, change your address, or temporarily deactivate your subscription, please go to http://v2.listbox.com/member/?[EMAIL PROTECTED]
