The Least Action Principle (LAP) is widely applied to search for solutions to prob-lems of classical mechanics. It claims that if an infinitesimal change does not affect the action of a system, that action would be the least action. In classical mechanics, if a particle moves from point A to point B, it will search for the path that requires the least energy consumption. Modeling physical phenomena utilizing LAP helps to predict an equation of motion and this principle is applicable for all known systems.
In this dissertation, we use the maximum independent set from graph theory as a guiding principle to model for least action. It is shown that the maximum independence number will correspond to the least action. We demonstrate the use of the LAP in infor-mation theory and its use in the modeling and the analysis of systems. Thus, we will have a general model which is applicable to any known system.
We have applied the LAP model to the Conant network decomposition technique. We demonstrated the applicability of our model in our case study that the Conant network decomposition technique computes the least action of the given network of the given data set.
Keywords: System modeling, Least action, Information theory, Graph theory, Network-ing |