From: ben.usenet@bsb.me.uk   
      
   Ben Bacarisse  writes:   
      
   > Malcolm McLean  writes:   
   >   
   >> You have a list of candidates, ranked by score. You want to try them   
   >> out in order, with the better candidates being tried first. However   
   >> you don't want the process to be deterministic - each run should yield   
   >> a separate order. And you want even low-ranked candidates to have some   
   >> chance of being tried early.   
   >>   
   >> Is there a partial sort / partial shuffle which can achieve this?   
   >   
   > Let me check is I know what you mean.  You have a list of words with   
   > scores   
   >   
   >   12 apple   
   >   10 cat   
   >    9 dog   
   >    8 egg   
   >    5 fox   
   >   
   > and you want a quasi-sort that might just (but very very rarely)   
   > produce   
   >   
   >    5 fox   
   >    8 egg   
   >    9 dog   
   >   10 cat   
   >   12 apple   
   >   
   > but will produce these orderings much more frequently:   
   >   
   >   12 apple    10 cat       10 cat   
   >    9 dog       9 dog       12 apple   
   >   10 cat      12 apple      8 egg   
   >    8 egg       8 egg        5 fox   
   >    5 fox       5 fox        9 dog   
   >   
   > ?  First thought.  Have a random field, r, that is chosen from a normal   
   > distribution prior to each sort.  Then sort by score+r.  By adjusting   
   > the distribution's parameters, you will get different probabilities of   
   > re-arrangement from almost none (with, say, mean=0, sdev=0.1) to chaotic   
   > when mean=1000 sdev=10000.   
      
   First thought was too fast!  You don't really need to change the mean.   
   0 will do just fine.  Changing the standard deviation will change the   
   degree of mixing.   
      
   --   
   Ben.   
      
   --- SoupGate-Win32 v1.05   
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