Generative sciences
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The '''generative sciences''' (or '''generative science''') are the interdisciplinary and multidisciplinary [[science]]s that explore the natural [[world]] and its complex behaviours as a generative process. Generative science shows how deterministic and finite rules and parameters in the natural phenomena interact with each other to generate indeterministic and infinite behaviour.
These sciences include [[psychology]] and [[cognitive science]], [[cellular automata]], [[generative linguistics]], [[natural language processing]], [[social network]] analysis, [[process physics]], [[connectionism]], [[evolutionary biology]], [[self-organization]], [[neural network]] theory, [[communication]] networks, [[cognitive musicology]], [[information theory]], [[systems theory]], [[genetic algorithm]]s, [[artificial life]], [[chaos theory]], [[complexity theory]], [[epistemology]], [[systems thinking]], [[genetics]], [[philosophy of science]], [[cybernetics]], [[bioinformatics]], and [[catastrophe theory]].
==Elemental perspective==
Generative sciences explores the natural phenomena at several levels including [[nature|physical]], biological and [[social]] processes as [[Emergence|emergent processes]]. It explores complex natural processes as generating through continuous interactions between elemental entities on parsimonious and simple universal rules and parameters.
==Scientific and philosophical origins==
The generative sciences originate from the [[monadology|monadistic]] philosophy of [[Leibniz]]. This was further developed by the neural model of [[Walter Pitts]] and [[Warren McCulloch]]. The development of computers or [[Turing Machine]]s laid a technical source for the growth of the generative sciences. However, the cornerstones of the generative sciences came from the work on [[cellular automaton]] theory by [[John Von Neumann]], which was based on the [[Walter Pitts]] and [[Warren McCulloch]] model of the [[neuron]]. Cellular automata were mathematical representations of simple entities interacting under common rules and parameters to manifest complex behaviors.
The generative sciences were further unified by the [[cybernetics]] theories of [[Norbert Wiener]] and the [[information theory]] of [[Claude E. Shannon]] and [[Warren Weaver]] in 1948. The mathematician Shannon gave the theory of the ''bit'' as a unit of [[information]] to make a basic decision, in his paper ''A mathematical theory of communication'' (1948). On this was further built the idea of uniting the physical, biological and social sciences into a holistic discipline of Generative Philosophy under the rubric of General Systems Theory, by [[Bertalanffy]], [[Anatol Rapoport]], [[Ralph Gerard]], and [[Kenneth Boulding]]. This was further advanced by the works of [[Stuart Kauffman]] in the field of [[self-organization]]. It also has advanced through the works of [[Heinz von Foerster]], [[Ernst von Glasersfeld]], [[Gregory Bateson]] and [[Humberto Maturana]] in what came to be called [[constructivist epistemology]] or radical constructivism.
The most influential advance in the generative sciences came from the development of the [[cognitive science]]s through the theory of [[generative grammar]] by the American linguist [[Noam Chomsky]] (1957). At the same time the theory of the [[perceptron]] was advanced by [[Marvin Minsky]] and [[Seymour Papert]] at [[MIT]]. It was also in the early 1950s that Crick and Watson gave the double helix model of the [[DNA]], at the same time as psychologists at the MIT including [[Kurt Lewin]], [[Jacob Ludwig Moreno]] and [[Fritz Heider]] laid the foundations for [[group dynamics]] research which later developed into [[social network]] analysis.
In 1996 [[Joshua M. Epstein]] and Robert Axtell wrote the seminal work ''Sugarscape''. In their work they expressed the idea of ''Generative science'' which would explore and simulate the world through generative processes.
==Prospective directions==
Generative scientists are working towards further developments and new frontiers. Latest and emerging directions in the generative sciences include the [[computer simulation]]s of complex social process, artificial life and [[Boids]]. The modeling of strategic decision making in cognitive organization psychology and the emergence of communication patterns in [[Cognitive organization theory]]. The research on anaphora in natural language processing is an important step towards the advancement of [[Artificial intelligence]] which is also influencing Process physics and semantic network modeling of physics and physical properties. Dynamical cognitive [[evolutionary psychology]] and [[dynamical psychology]] is the latest direction in the systematic unification of the psychological sciences. This is further expanded through the mathematical theories of the Cognitive grammar of [[music]].
==Prominent generative scientists==
* [[John Von Neumann]]
* [[Noam Chomsky]]
* [[Robert Axelrod]]
* [[Walter Pitts]]
* [[Norbert Wiener]]
* [[John Holland]]
* [[Marvin Minsky]]
* [[Ray Jackendoff]]
* [[John Horton Conway]]
==Selected bibliography==
# W. Weaver and C. E. Shannon, (1948) The Mathematical Theory of Communication, Urbana, Illinois: University of Illinois Press.
# Chomsky N (1957) Syntactic Structures. The Hague: Mouton.
# Warren McCulloch and Walter Pitts,(1943) A Logical Calculus of Ideas Immanent in Nervous Activity, Bulletin of Mathematical Biophysics 5:115-133.
# Lewin, K. (1951) Field theory in social science; selected theoretical papers. D. Cartwright (Ed.). New York: Harper & Row.
# Weiner N (1948) Cybernetics; John Wiley, New York, 1948.
# von Neumann, Jon (1966) The Theory of Self-Reproducing Automata, edited and completed by Arthur W. Burks (Urbana, IL: University of Illinois Press).
# Rapoport, A. (1953). Spread of information through a population with sociostructural bias: I. Assumption of transitivity. Bulletin of Mathematical Biophysics, 15, 523-533.
# James L. McClelland and David E. Rumelhart. (1987) Explorations in Parallel Distributed Processing Handbook. MIT Press, Cambridge, MA, USA, 1987.
# Gleick, James (1987); [[Chaos: Making a New Science]]; Copyright 1987, Viking, N.Y.
# Jackendoff, Ray, and Fred Lerdahl (1981). "Generative music and its relation to psychology." Journal of Music Theory 25(1): 45-90
# Allen, T.J. (1970). Communication networks in R&D laboratories. R&D Management, 1(1), 14-21.
# Skvoretz, J. 2002. Complexity Theory and Models for Social Networks. Complexity 8: 47-55
# Seidman, Stephen B. (1985). Structural consequences of individual position in nondyadic social networks, Journal of Mathematical Psychology, 29: 367-386
# Thietart, R. A., & Forgues, B. (1995). Chaos theory and organization. Organization Science, 6, 19-31.
# Holland, John H., "Genetic Algorithms", Scientific American, July 1992, pp. 66-72
# Albert-Laszlo Barabasi and Eric Bonabeau, "Scale-Free Networks", Scientific American, May 2003, pp 60-69
# T. Winograd, Understanding Natural Language, Academic Press, New York, 1972.
# M. Minsky, The Society of Mind, Simon and Schuster, New York, 1986.
# Reginald T. Cahill, Christopher M. Klinger and Kirsty Kitto (2000) Process Physics: Modelling Reality as Self-Organising Information; Published in The Physicist, 37(6), 191-195.
# Epstein J.M. and Axtell R. (1996) Growing Artificial Societies - Social Science from the Bottom. Cambridge MA, MIT Press.
# Epstein J.M. (1999) Agent Based Models and Generative Social Science. Complexity, IV (5)
# Kaneko K. (1998) Life as Complex System: Viewpoint from Intra-Inter Dynamics. Complexity, 6, pp.53-63.
# Robert Axtell, Robert Axelrod, Joshua Epstein, and Michael D. Cohen, (1996) Aligning Simulation Models: A Case Study and Results; Computational and Mathematical Organization Theory, 1, pp. 123-141 (http://www-personal.umich.edu/~axe/research/Aligning_Sim.pdf)
# McTntyre L. (1998) Complexity: A Philosopher's Reflection. Complexity, 6, pp.26-32.
==See also==
* [[Artificial life]]
* [[Emergence]]
* [[Complex system]]
* [[Boids]]
* [[Connectionism]]
==External links==
* http://www.swarthmore.edu/socsci/tburke1/artsoc.html (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]]
[[Category:Cognitive science]]
[[Category:Interdisciplinary fields]]