Another way to say why there is a phase transition to instability there is that it is inherent in pushing learning tasks to exceed their response times. Becoming incoherent in response is a kind of system failure that leads to systems to collapse for any critical part. That is part of that learning theorem I presented graphically 30 years ago. http://www.synapse9.com/pub/theInfiniteSoc.pdf
It's now more simply stated as just that the limit of learning is unexpected complications, an environmental signal you can not include in your plan, model or theory. It's particularly useful as the corollary that growth processes will lead to collapse unless the way they are changed by running into limits is by developing stability instead. The fix? Learn when to expect complications and how to see them coming. Phil > -----Original Message----- > From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On > Behalf Of glen e. p. ropella > Sent: Wednesday, October 01, 2008 11:29 AM > To: 'The Friday Morning Applied Complexity Coffee Group' > Subject: [FRIAM] This Economy Does Not Compute > > > http://www.nytimes.com/2008/10/01/opinion/01buchanan.html?_r=3&ref=opin > ion&oref=slogin&oref=slogin&oref=slogin > > -- > glen e. p. ropella, 971-219-3846, http://tempusdictum.com > > > ============================================================ > FRIAM Applied Complexity Group listserv > Meets Fridays 9a-11:30 at cafe at St. John's College > lectures, archives, unsubscribe, maps at http://www.friam.org ============================================================ FRIAM Applied Complexity Group listserv Meets Fridays 9a-11:30 at cafe at St. John's College lectures, archives, unsubscribe, maps at http://www.friam.org
