> 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.
yeah, this is handled in Novamente via the "revision rule" and "rule of choice", two inference rules. If two estimates are reasonably close, they are weighted-averaged in a certain way; if they are very different, they may both be maintained pending future evidence that one of them is totally wrong... The Novamente situation is a little subtler because in addition to probabilities we retain for each probability a number indicating the "amount of evidence" on which the probability is based. This can be useful, e.g. for the weighting in the above-mentioned weighted average rule. But anyway, using the weighted-averaging rule dynamically and iteratively can lead to problems in some cases. Maybe the mechanism you suggest -- a nonlinear average of some sort -- would have better behavior, I'll think about it. -- Ben ------- To unsubscribe, change your address, or temporarily deactivate your subscription, please go to http://v2.listbox.com/member/?[EMAIL PROTECTED]
