Dimensional Analysis of the Idée-Force of Social Agents with Constrained Optimization from Remote Sensing

Abstract

Dimensional analysis of societal behavior is divided into hierarchical fields of spaces, such as economics. Social agents create strategies to adapt to their habitus. Within a particular field, the learned doxa influences the agent’s thoughts and subsequent actions. The meme(s) produce an idée-force that can be calibrated, as a dimensionless quantity, from data gathered by remote sensing. The technological process of remote sensing involves collecting and collating all relevant recorded writings, audio and visual data from any era of time where sufficient information can be mined. That data can be analyzed by constrained optimization which determines the max and min of x and y, given max l (x,y) = ƒ(x,y) + λg(x,y) and min l (x,y) = ƒ(x,y) - λg(x,y) such that g(x,y) ≥ 0. A decision matrix of the objective function value (max ƒ(x,y) and min ƒ(x,y)) can satisfy inequality within two (absolute) value terms of dimensionless numbers. The four options for the range of x,y are min,min or (0,0), max,min or (> 0,0), min,max or (0, > 0), and max,max (> 0, > 0). Maximizing the optimized subject to a set or series of constrains allow for the decisions to be analyzed for future simulations and predictions.