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.[2] An example field of study is how unintended consequences arise in social processes.
Generative sciences often explore natural phenomena at several levels of organization.[3][4] Self-organizing natural systems are a central subject, studied both theoretically and by simulation experiments. The study of complex systems in general has been grouped under the heading of "general systems theory", particularly by Ludwig von Bertalanffy, Anatol Rapoport, Ralph Gerard, and Kenneth Boulding.
- ^ Gordana Dodig-Crnkovic; Raffaela Giovagnoli (2013), "Computing Nature – A Network of Networks of Concurrent Information Processes", in Gordana Dodig-Crnkovic; Raffaela Giovagnoli (eds.), Computing nature: Turing centenary perspective, Springer, p. 7, ISBN 978-3-642-37225-4
- ^ Ning Nan; Erik W. Johnston; Judith S. Olson (2008), "Unintended consequences of collocation: using agent-based modeling to untangle effects of communication delay and in-group favor", Computational and Mathematical Organization Theory, 14 (2): 57–83, doi:10.1007/s10588-008-9024-4, S2CID 397177
- ^ Farre, G. L. (1997). "The Energetic Structure of Observation: A Philosophical Disquisition". American Behavioral Scientist. 40 (6): 717–728. doi:10.1177/0002764297040006004. S2CID 144764570.
- ^ J. Schmidhuber. (1997) A computer scientist's view of life, the universe, and everything. Foundations of Computer Science: Potential – Theory – Cognition, Lecture Notes in Computer Science, pages 201–208, Springer