Research on Individual Learning Systems

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Revision as of 18:13, 8 November 2008 by Pfhenshaw (talk | contribs) (References)
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The general subject of dissipative systems is not really new, and really vast, but the recognition that the ones that begin and end do not need to be approximated by deterministic models in order to explore their changing local organization and developmental behaviors is quite new, to the public discussion of natural systems at least. It's learning how to be a naturalist using the tools of physics.

The starting point is that the conservation laws seem to imply that processes need to have multiple scales of developmental organization for energy flows to begin or end. It's the old problem that when theory implies infinite field density, rates of energy flow or accelerations, the real implication is of another scale of organization. principle of continuity and divergence.

To apply that to systems physics research one uses the principle as if backwards from the normal procedures of physics. It becomes a diagnostic tool for exploratory learning, and identifying the 'little bangs' and 'big booms' of locally developmental processes as they explore their interaction with their environments. It leads to a diagnostic approach to physical systems and change rather than a representational approach. Some work on this approach was begun by Phil Henshaw in the 1970's collected on his web site.

A diagnostic approach to physics treats the physical system as an "in-physico" model of itself... i.e. that what you start with is the full complete and true representation of the system, and then one explores it's features and shapes to inform one's questions about it to fit to its shapes like a glove. It's an approach of trying to understand what nature has already built, by developing better questions about what is in the process of developing, and what new conditions it will be responding to as it develops further. The conserved property of derivative continuity allows one to do that by connecting inflection points in its learning processes with its internal network of its processes and the environment they are adapting to. Typically there is a switch in the development path between a starting period of self-referencing change, without limits, to responding to and becoming part of the limits of a larger environment as the original conditions are altered by the system's own changes.


Henshaw 2008 A principle of continuity and divergence.

Henshaw 2008 Life’s hidden resources for learning in Cosmos & History special 10/08 issue on "What is Life"

Henshaw 1999-1 Features of derivative continuity in shape International Journal of Pattern Recognition and Artificial Intelligence (IJPRAI), special issue on invariants in pattern recognition, V13 No 8 1999 1181-1199 - mathematical methods for identifying and reconstructing continuity in natural flows