A Computational Model of Human Personalities (Dataset)

In this paper we present a method for programming human personalities. We first describe a plausible biological mechanism that provides a logical explanation of the model in terms of power flow in the brain. We then show how the model qualitatively predicts the personality characteristics described by Lowry Colors, Enneagram, Merrill's C.A.P.S., the five factor model, and the clinical personality disorders. Regardless of the truth of the biological model, the predicted configuration allows us to create a feedback-loop computational model of human personalities, using the Enneagram to describe self-images and Myers-Briggs to describe behavioural techniques. The model successfully predicts the distribution of Myers-Briggs personality types in the human population within 14 percent error. The model directly results in the ability to program personalities on robots and AI systems. Moreover, the model suggests where to look for the source of personalities in the operation of biological brains. Run the file main.m.