Study of how complex behaviour can be generated by deterministic and finite rules and parameters
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.
The development of computers and
automata theory laid a technical foundation for the growth of the generative sciences. For example:
Cellular automata are mathematical representations of simple entities interacting under
deterministic rules to manifest complex behaviours. They can be used to model emergent processes of the physical universe, neural cognitive processes and social behavior.[6][7][8][9]
Conway's Game of Life is a zero-player game based on cellular automata, meaning that the only input is in setting the initial conditions, and the game is to see how the system evolves.[10]
In 1996
Joshua M. Epstein and
Robert Axtell wrote the book Growing Artificial Societies which proposes a set of automaton rules and a system called Sugarscape which models a population dependent on resources (called sugar).
Artificial neural networks attempt to solve problems in the same way that the human brain would, although they are still several orders of magnitude less complex than the human brain and closer to the computing power of a worm. Advances in the understanding of the human brain often stimulate new patterns in neural networks.
One of the most influential advances in the generative sciences as related to
cognitive science came from
Noam Chomsky's (1957) development of
generative grammar, which separated language generation from semantic content, and thereby revealed important questions about human language. 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.
See also
Generative systems – Technologies that can produce change driven by audiences
References
^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,
ISBN978-3-642-37225-4
^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,
S2CID397177
^Farre, G. L. (1997). "The Energetic Structure of Observation: A Philosophical Disquisition". American Behavioral Scientist. 40 (6): 717–728.
doi:
10.1177/0002764297040006004.
S2CID144764570.