From: mailbox@dmitry-kazakov.de   
      
   On 21 Jun 2006 06:46:35 -0700, makc.the.great@gmail.com wrote:   
      
   > let's say we have some reasoning program that constantly draws out some   
   > conclusions based on results of its own previous conclusions. what   
   > choise of functions will guarantee that resulting values will not "flat   
   > out" to 0 or "squeeze up" to 1 just because they have been put through   
   > too many iterations?   
      
   This is an interesting problem. I think that there is no such function in   
   the following sense. The model is inadequate. The assumption that the facts   
   which the conclusions are inferred from are not stable. So each new   
   iteration can potentially add contradictions to the knowledge base.   
   Inference can handle contradictions either by consensus or gullibility   
   operations, but in the end, it will anyway decline to either "dunno" or   
   "rubbish". I think that the only way out is to change the model, i.e. to   
   give a time aspect to the knowledge. So that the inference would deal with   
   P(t1), Q(t2) => R(t0) rather than just P, Q => R. The model should then   
   describe how, say, delta t=t0-t1 influences confidence in P. The goal would   
   be to let more fresh facts to override old ones if they contradict each   
   other, or to approve each other otherwise.   
      
   --   
   Regards,   
   Dmitry A. Kazakov   
   http://www.dmitry-kazakov.de   
      
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