Systems, Complex Systems, and Intelligence: an Educational Overview

Abstract

This contribution examines, for didactic purposes, the peculiarities of systems that have the ability to acquire, maintain and deactivate properties that cannot be deduced from those of their components. We evaluate complex systems that can acquire, lose, recover, vary the predominance of property sequences, characterized by their predominant coherence and variability, through the processes of self-organization and emergence, when coherence replaces organization. We consider correspondingly systemic epistemology as opposed to the classical analytic approach and to forms of reductionism. We outline aspects of the science of complexity such as coherence, incompleteness, quasiness and issues related to its modeling. We list and consider properties and types of complex systems. Then we are dealing with forms of correspondence that concern the original conception of intelligence of primitive artificial intelligence, which was substantially based on the high ability to manipulate symbols, and of those of a complex nature that consider emergent processes, such as inference, the learning, reasoning and memory. Finally, the recognition and acquisition of forms of intelligence in nature is explored, with particular reference to its emerging systemic processes.