Organodynamics

Grant Holland, Apr 25, 2014

Slide: Tractability and Organodynamic Modeling
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Tractability and complexity are clearly issues with organodynamic modeling:

á      Enumerating the sample points (organizations)

á      Articulating each as an extended topology

á      Forming the joint distribution (OPDs)

á      Assigning the simple and joint distributions (ODPDs)

á      Defining the Markov processes (ODSPs)

 

Organodynamics efforts to respect the ontology (fundamental nature) of the systems it models:

 

As organizations of interrelationships. Because they ARE organizations, not numbers or vectors.

 

A biological cell IS a set of interrelationships. It HAS many attributes, some of which are numerical.

 

Modeling target systems as organizations is more complex than modeling them as vectors of numbers (manifolds).

 

Model Fidelity

 

Models exist to enhance intellectual accessibility while conserving salient features.

 

They must hit a midpoint between two extremes:

1.    If too complex, a model loses intellectual accessibility.

2.    If too simple, it can fail to conserve salient features.

 

The target systems that organodynamics seeks to model are extraordinarily complex. Hitting this midpoint remains highly complex.

 

Organodynamic models should be Òas simple as possible, but no simpler.Ó

 

Incremental Modeling:

 

á      Course Graining

á      Theoretical Probability Assignments

á      Theoretical Probability Refinements

 

 

Organodynamics is not alone in facing seemingly-intractable modeling challenges:

 

Statistical mechanics faced many of the same issues.

 

Many of the incremental modeling approaches mentioned in the previous panel are taken from statistical mechanics.

 

Notes: