On computations and strategies for real and artificial systems

A challenge in reproducing life is to reproduce cognition. We propose a methodology by which human actions are analyzed in a real-setting and are then used to evolve artificial neural networks capable of reproducing these actions. It is also demonstrated that analyzing human actions can be used for skill-assessment, where we introduce a model for in-silico computational psychology to assess skills and competency of human plays. The same methodologies can be used by coaches and mentors to diagnose skills for their players and juniors in an attempt to improve their abilities. Results demonstrate interesting patterns in the way expert players develop their skills overtime and that it is possible to reproduce these skills in an artificial context.