Thanks for the link. I agree that this work is moving in an interesting direction, though I'm afraid that for AGI (and adaptive systems in general), TM may be too low as a level of description --- the conclusions obtained in this kind of work may be correct, but not constructive enough. Even so, I'll be interested in how far they can go.
You may be interested in the works of Peter Kugel (http://www.cs.bc.edu/~kugel/Publications/Publications.html). My own comment on TM is at http://nars.wang.googlepages.com/wang.computation.pdf Pei On 10/30/07, William Pearson <[EMAIL PROTECTED]> wrote: > I have recently been trying to find better formalisms than TMs for > different classes of adaptive systems (including the human brain), and > have come across the Persistent Turing Machines[1], which seem to be a > good first step in that direction. > > They have expressiveness claimed to be greater than TM[2], although I > have not had a chance to go through the proof, I can see the > possibility as they can change the function of the input to output mid > computation so may not be subject to the same problems of halting as > TM. Although if you include the input history as well as the > specification of a PTM in the code you are trying to prove statements > about, you can probably construct similar questions it cannot answer. > > Has there been any other work towards the goal of better taxonomies > for adaptive systems? > > Will Pearson > > [1] http://www.cs.brown.edu/people/dqg/Papers/wurzburg.ps > [2] http://www.cse.uconn.edu/~dqg/papers/its.pdf > > ----- > This list is sponsored by AGIRI: http://www.agiri.org/email > To unsubscribe or change your options, please go to: > http://v2.listbox.com/member/?&; > ----- This list is sponsored by AGIRI: http://www.agiri.org/email To unsubscribe or change your options, please go to: http://v2.listbox.com/member/?member_id=8660244&id_secret=59017875-20235f
