Generative science

Generative science is an area of research that explores the natural world and its complex behaviours.

It explores ways "to generate apparently unanticipated and infinite behaviour based on deterministic and finite rules and parameters reproducing or resembling the behavior of natural and social phenomena".

[1] By modelling such interactions, it can suggest that properties exist in the system that had not been noticed in the real world situation.

The development of computers and automata theory laid a technical foundation for the growth of the generative sciences.

It was also in the early 1950s that psychologists at the MIT including Kurt Lewin, Jacob Levy Moreno and Fritz Heider laid the foundations for group dynamics research which later developed into social network analysis.

Interaction between a few simple rules and parameters can produce endless, seemingly unpredictable complexity.
Turbulence in the tip vortex from an airplane wing. Studies of the critical point beyond which a system creates turbulence were important for chaos theory , analyzed for example by the Soviet physicist Lev Landau who developed the Landau-Hopf theory of turbulence . David Ruelle and Floris Takens later predicted, against Landau, that fluid turbulence could develop through a strange attractor , a main concept of chaos theory.
Computer simulation of the branching architecture of the dendrites of pyramidal neurons . [ 5 ]
The natural phenomenon of herd behaviour as in a flock of birds can be modelled artificially using simple rules in individual units, with swarm intelligence rather than any centralized control.