Elements of Cognitive Systems Theory

Abstract

The brain is without doubt the most complex adaptive system known to humanity, arguably also a complex system about which we know very little. Throughout this book we have considered and developed general guiding principles for the understanding of complex networks and their dynamical properties; principles and concepts transcending the details of specific layouts realized in real-world complex systems. We follow the same approach here, considering the brain as just one example of what is called a cognitive system, a specific instance of what one denotes, cum grano salis, a living dynamical system. In the first part we will treat general layout considerations concerning dynamical organizational principles, an example being the role of diffuse controlling and homeostasis for stable long-term cognitive information processing. Special emphasis will be given to the motivational problem – how the cognitive system decides what to do – in terms of survival parameters of the living dynamical system and the so-called emotional diffusive control. In the second part we will discuss two specific generalized neural networks implementing various aspects of these general principles: a dense and homogeneous associative network (dHAN) for environmental data representation and associative thought processes, and the simple recurrent network (SRN) for concept extraction from universal prediction tasks.