Cognitive control in cognitive dynamic systems: A new way of thinking inspired by the brain

Abstract

Briefly, main purpose of the paper is fourfold: a) Cognitive perception, which consists of two functional blocks: improved sparse-coding under the influence of perceptual attention for extracting relevant information from the observables and ignoring irrelevant information, followed by a Bayesian algorithm for state estimation. b) Entropic state of the perceptor, which provides feedback information to the controller. c) Cognitive control, which also consists of two functional blocks: executive learning algorithm computed by processing the entropic state, followed by predictive planning to set the stage for policy to act on the environment, thereby establishing the global perception-action cycle. d) Experimental results for exploiting the perceptual as well as executive attention in a co-operative manner, which is aimed at the first demonstration of risk control in the presence of a severe disturbance in the environment.