Complexity

Our vision states that nature, artificial systems and societies alike are all populated by multiple types of autonomous agents, as for instance cells, living organisms, software, human beings or social groups, which continuously interact with other agents and take decisions based on their perceptions of the environment and their acquired knowledge, whether explicit or, more generally, derived from a particular culture.

The irreducible autonomy of those decisions is the fundamental basis for new ways of addressing the ultimate goal of science.

Probably the most important concept this analysis provides is that of Emergence. The Science of Complexity could also be called the Science of Emergence: out of the complex interactions between the different parts of a system and with its environment, original properties and behaviours do emerge, which were not deductible from the sole properties of the parts. In the end, the whole is actually much more than the sum of its parts.

Emergence expresses itself in ubiquitous but astonishing capabilities of nature and mankind: self-replication and self-organization, perception and learning, adaption and development of purpose. The very basics of life itself, as well as consciousness or social institutions, are some results of the mechanisms of emergence which have been acting, with unpredictable results, since the beginning of times.

Complexity Science is in itself an emergent phenomenon.

Nurtured by diverse disciplines, most notably General Systems Theory, Non-Equilibrium Thermodynamics, Dynamical Systems Analysis and Cybernetics, this science was born in the academic world in the mid-seventies and has been enriched since then by cross-fertilization between those disciplines and applications in engineering, neurobiology, anthropology, sociology or economics, among others.

Nowadays, through the active collaboration of many researchers all over the world, Complexity Science goes on opening horizons to analyze the behaviour of much diverse systems, whether natural or artificial, and using paradigms based on autonomous agents, multi-agent systems or multi-layer, multi-scale meta-systems, in order to represent such elusive phenomena as the earth climate or the evolution of human societies.

On these grounds, the INNAXIS Institute works to produce new knowledge and to apply the existing one to the generation of socially helpful innovations