Editing Generative science

{{short description|Study of how complex behaviour can be generated by deterministic and finite rules and parameters}}
[[File:Game of life torus 100 100 1500.gif|right|500px|thumb|Interaction between a few simple rules and parameters can produce endless, seemingly unpredictable complexity.]]

'''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 automaton|deterministic]] and [[Finite-state machine|finite]] rules and parameters reproducing or resembling the behavior of natural and social phenomena".<ref>{{citation |page=7 |chapter=Computing Nature – A Network of Networks of Concurrent Information Processes |author1=Gordana Dodig-Crnkovic |author2=Raffaela Giovagnoli |title=Computing nature: Turing centenary perspective |publisher=Springer |year=2013 |editor1=Gordana Dodig-Crnkovic |editor2=Raffaela Giovagnoli |isbn=978-3-642-37225-4}}</ref> By modelling such interactions, it can suggest that properties exist in the system that had not been noticed in the real world situation.<ref name= "Ning">{{citation |author=Ning Nan |author2=Erik W. Johnston |author3=Judith S. Olson |year=2008 |title=Unintended consequences of collocation: using agent-based modeling to untangle effects of communication delay and in-group favor |journal=Computational and Mathematical Organization Theory |volume=14 |issue=2 |pages=57–83 |doi=10.1007/s10588-008-9024-4|s2cid=397177 }}</ref> An example field of study is how [[unintended consequences]] arise in social processes.

Generative sciences often explore natural phenomena at several levels of organization.<ref>{{Cite journal | last1 = Farre | first1 = G. L. | title = The Energetic Structure of Observation: A Philosophical Disquisition | doi = 10.1177/0002764297040006004 | journal = American Behavioral Scientist | volume = 40 | issue = 6 | pages = 717–728 | year = 1997 | s2cid = 144764570 }}</ref><ref name= "Schmidhuber">J. Schmidhuber. (1997) [https://arxiv.org/abs/quant-ph/9904050 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</ref> [[Self-organization|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]].

==Scientific and philosophical origins==
[[File:Airplane vortex edit.jpg|thumb|[[Turbulence]] in the [[Wingtip vortices|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 physicists|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.]]
[[File:Forest of synthetic pyramidal dendrites grown using Cajal's laws of neuronal branching.png|thumb|200px|[[Computer simulation]] of the branching architecture of the [[dendrite]]s of [[pyramidal neuron]]s.<ref>{{Cite journal |author=Hermann Cuntz | doi = 10.1371/image.pcbi.v06.i08 | title = PLoS Computational Biology Issue Image &#124; Vol. 6(8) August 2010 | journal = PLOS Computational Biology | volume = 6 | issue = 8 | pages = ev06.ei08 | year = 2010 | doi-access = free }}</ref>]]
[[File:Auklet flock Shumagins 1986.jpg|right|200px|thumb|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.]]

The development of computers and [[automata theory]] laid a technical foundation for the growth of the generative sciences. For example:
*[[Cellular automaton|Cellular automata]] are mathematical representations of simple entities interacting under [[determinism|deterministic]] rules to manifest complex behaviours.  They can be used to model emergent processes of the physical universe, neural cognitive processes and social behavior.<ref name="Kenrick">{{cite journal | doi = 10.1037/0033-295X.110.1.3 | last1 = Kenrick | first1 = DT | last2 = Li | first2 = NP | last3 = Butner | first3 = J | title = Dynamical evolutionary psychology: individual decision rules and emergent social norms | journal = Psychological Review | volume = 110 | issue = 1 | pages = 3–28 | year = 2003 | pmid = 12529056 | citeseerx = 10.1.1.526.5218 | s2cid = 43306158 }}</ref><ref name="EpsteinAxtell">{{cite book|first1=Joshua M.|last1=Epstein|author-link1=Joshua M. Epstein|first2=Robert L.|last2=Axtell|author-link2=Robert Axtell|year=1996|title=Growing Artificial Societies: Social Science From the Bottom Up|publisher=MIT/Brookings Institution|location=Cambridge MA|page=[https://archive.org/details/growingartificia00epst/page/224 224]|isbn=978-0-262-55025-3|url-access=registration|url=https://archive.org/details/growingartificia00epst/page/224}}</ref><ref name= "Nowak">{{citation |author=Nowak A. |author2=Vallacher R.R. |author3=Tesser A. |author4=Borkowski W. |year=2000 |title=Society of Self: The emergence of collective properties in self-structure |journal=Psychological Review |volume=107 |issue=1 |pages=39–61 |pmid=10687402 |doi=10.1037/0033-295x.107.1.39}}</ref><ref name= "Epstein">{{citation |author=Epstein J.M. |year=1999 |title=Agent Based Computational Models and Generative Social Science |journal=Complexity |volume=4 |issue=5 |pages=41–60 |doi=10.1002/(SICI)1099-0526(199905/06)4:5<41::AID-CPLX9>3.0.CO;2-F|bibcode=1999Cmplx...4e..41E |citeseerx=10.1.1.353.5950 }}</ref>
**[[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.<ref>[http://www.bitstorm.org/gameoflife/ John Conway's Game of Life]</ref>
**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 network]]s 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 ==
* {{annotated link|Generative systems}}

==References==
{{Reflist|30em}}

==External links==
* http://www.swarthmore.edu/socsci/tburke1/artsoc.html {{Webarchive|url=https://web.archive.org/web/20050409235016/http://www.swarthmore.edu/socsci/tburke1/artsoc.html |date=2005-04-09 }} (Artificial Societies, Virtual Worlds and the Shared Problems and Possibilities of Emergence)
* http://jasss.soc.surrey.ac.uk/JASSS.html (The Journal of Artificial Societies and Social Simulation)

[[Category:Systems theory]]