Organodynamics

Grant Holland, Apr 25, 2014

Slide: Wrapup

 Nav    Refs    Top    Bottom    Previous    Next

90m        90m

45m        45m

25m        25m


 

1. Organodynamics is

A dynamical systems theory, where

a.   State = organization

b.   Trajectory = reorganization

c.   Trajectory is a stochastic process

d.   Trajectory is a chance variable that is not necessarily a random variable



2. Information Theory provides the mathematical foundation of organodynamics.

A number of entropic functionals measure the degree of uncertainty of stochastic dynamics. These are: entropy, joint entropy, conditional entropy, relative entropy, mutual information and entropy rate.

Like the moments and central moments of mathematical statistics, these entropic functionals characterize the degree of chance variation - but use only probabilities as inputs.

The key to constrained or controlled dynamics is stochastic dependence.

In organodynamics, a dependent stochastic process that is called an organodynamic dependent stochastic process, or ODSP describes the dynamics of a target application.

 3. Organodynamics combines organizational dynamics with entropic functionals to model biological and other highly complex dynamical processes perhaps more faithfully WRT organizational state and stochastic dynamics than nonlinear dynamics.

Organodynamics does this by defining: OSS, OPS, OPD, ODPD, OSP and ODSP - and by characterizing long-term behavior in the ODSP.

An ODSP is a dependent, or conditional, stochastic process - e.g. a Markov process - whose sample points are extended topologies as defined by organodynamics.  One of these ODSPs defines the dynamics of an organodynamics application.

Defining the dynamics of the application amounts to defining the transition matrices of an ODSP.

 

Organodynamics seeks to be a complex adaptive dynamical systems theory that describes the dynamics of a certain class of highly complex systems by probability alone.


I am presently engaged in "reverse-engineering" evolutionary biology to understand in detail the stochastic mechanisms that drive constraint, adaptation and persistence in biological systems.


Articulated using the constructs of organodynamics, this effort should improve the level of detail of this general, theory.

 

Notes: