Abstract
A model of a spatio-cultural sub-context (enfolded in a wider scope context) is presented in the form of a blue print of a Complex System with a two-stage decision engine at its core. The engine first attaches a meaning to analyzable datum, and then decides whether to keep or change it. It does not alter already stored meanings but is designed to search for data to be converted into additional stored meanings and improve the accuracy of correspondence of their spatial and cultural range of relevance. Meaning is reduced to the choice of a strategy—a future continuum of events; a choice dependent on a unique Evolutionary Path, a past continuum of events specific enough to lead to the current temporarily stable state of a spatio-cultural category. It is a blue print for a program that can emulate decisions to initiate changes in the environment in which a collective of culture partners resides; changes consisting of movements from one location to another or in the layout of its current location. The model is proposed at a low cultural resolution and is applicable, after suitable modifications, to a majority of city/period pairs. However, any such model has to be city/period specific. It is illustrated with a design for analyzing changes in the Israeli city, in particular in Tel Aviv.
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Abbreviations
- CS:
-
Complex system/s
- EP:
-
Evolutionary path
- MM:
-
Mental map/s
- POV:
-
Point of view
- ITh:
-
Information-theory
- IW:
-
Inner world
- RA:
-
Reactive animation
- SMV:
-
Space Modeling Vector
- TA:
-
Tel Aviv
- VF:
-
Visual formalism
References
Alon U. (2007) An introduction to systems biology: Design principles of biological circuits. Chapman & Hall, CRC, London
Anderson P. W. (1972) More is different. Science 177: 393–396
Atlan H., Cohen I. R. (1998) Immune information, self-organization and meaning. International Immunology 10(6): 711–717
Barbábasi A. L. (2003) Linked. PLUME, NY
Batty, M. (2008). Scaling, interactions, networks, dynamics and urban morphologies. In The encyclopedia of complexity & system science. Berlin: Springer. http://www.casa.ucl.ac.u.
Brand, S. (1997). How buildings learn: What happens to them after they’re built. Phoenix Illustrated (revised edition), London.
Benguigui, L. (1999). Computer simulation. In: D. Stauffer (Ed.), Urban geography. Annual Review of Computational Physics (Vol. VII, pp. 125–149).
Bohm D. (1992) Thought as a system. Routledge, London
Bohm D. (1996) On dialogue. Routledge, London
Ben Jacob, E., & Shapira, Y. (2010). Meaning-based natural intelligence vs. information-based. Artificial Intelligence (in press). http://star.tau.ac.il/~eshel/papers/meaning%20based.pdf.
Cohen I. R. (2004) Tending Adam’s garden: Evolving cognitive immune self. Elsevier, Amsterdam
Cohen I. R. et al (2006) Immune system computation and the immunological homunculus. In: Nierstrasz O. (eds) MoDELS 2006, LNCS 4199. Springer, Berlin/Heidelberg, pp 499–512
Cohen R., Erez K., Ben-Avraham D., Havlin S. (2000) Resilience of the internet to random breakdowns. Physical Review Letters 85: 4626
Dendrinos D.S., Sonis M. (1990) Chaos and socio-spatial dynamics. Applied Mathematical Sciences No. 86. Springer, New York
Even-Zohar, I. (2005). Papers in culture research. http://www.tau.ac.il/~itamarez/works/books/ez-cr2004.pdf.
Efroni S., Harel D., Cohen I. R. (2007) Emergent dynamics of thymocyte development and lineage determination. PLoS Computational Biology 3(1): e13. doi:10.1371/journal.pcbi.0030013
Fox Keller E. (2000) Models of, models for. Philosophy of Science 67(Suppl.): S72–S86
Fox Keller E. (2005) Revisiting “scale-free” networks. BioEssays 27: 1060–1068 Wiley Periodicals, Inc.
Gros C. (2008) Complex and adaptive dynamcial systems, Chapter 7: Elements of cognitive system theory. Springer, Berlin
Hägerstrand T. (1967) Innovation diffusion as a spatial process. Chicago University Press, Chicago
Haken H. (1999) Synergetic cities. Part IV self organization and the city. of J. Portugali (et~al.). Springer, Berlin
Harel D. (1987) Statecharts: A visual formalism for complex systems. Science of Computer Programming 8: 231–274
Harel D., Gery E. (1997) Executable object modeling with statecharts. Computer 30(7): 31–42 IEEE Press.
Hillier B. (1996) Space is the machine: A configurational theory of architecture. Cambridge University Press, Cambridge
Holland J. H. (1995) Hidden order: How adaptation builds complexity. Perseus, Cambridge, MA
Holland J. H. (1998) Emergence: From chaos to order. Perseus, Cambridge, MA
Jablonka E., Lamb J. (2004) Evolution in four dimensions: Genetic, epigenetic, behavioral and symbolic variation in the history of life. MIT Press, Cambridge, MA
Kauffman S. (1995) At home in the universe: The search for the laws of self-organization and complexity. Oxford University Press, New York
Kostof S. (1991) The city shaped: Urban patterns and meanings through history. Thames & Hudson, London
Kostof S. (1992) The city assembled: The elements of urban form through history. Thames & Hudson, London
Lakoff G. (1987) Women fire and dangerous things: What categories reveal about the mind. The University of Chicago Pres, Chicago
Lane, D. (2008). Artifacts and organization: A complexity perspective on innovation and social change. http://videolectures.net/eccs08_lane_aaoacpo.
Levin S. A. (2002) Complex adaptive systems: Exploring the known, the unknown and the unknowable. Bulletin of the American Mathematical Society 40(1): 3–19
Louzoun, Y., & Atlan, H. (2006). The emergence of goals in a self-organizing network: A non-mentalist model of intentional actions. Neural Networks, 20 (2007), 156–171. Elsevier.
Louzoun Y., Solomon S., Atlan H., Cohen I.R. (2003) Proliferation and competition in discrete biological systems. Bulletin of Mathematical Biology 65: 375–396 Elsevier.
Manson S.M. (2000) Simplifying complexity: A review of complexity theory. Geoforum 32(2001): 305–414 Pergamon.
Pumain, D., Paulus, F., Vacchiani-Marcuzzo, C., & Lobo, J. (2006). An evolutionary theory for interpreting urban scaling laws. Cybergeo: Revue européenne de géographie, 343. http://www.cybergeo.revues.org/index343.htm.
Rabinovich, M. I., Varona, P., Selverston, A. I., & Abarbanel, H. D. I. (2006). Dynamical principles in neuroscience. Reviews of Modern Physics, 78, October–December 2006, 1213–1264. The American Physical Society.
Shanon C. E., Weaver W. (1963) The mathematical theory of communication. University of Illinois Press, Chicago
Schweber S., Wächter M. (2000) Complex systems, modelling and simulation. Studies in History of Philosophy and Modern Physics 31(4): 583–609
Simon H. A. (1997) Administrative behavior. The Free Press, New York
Sonis M., Hewing G. J. D. (2009) Tool kits in regional science: Theory, models and estimation. Springer, Dodrecht
Watts D. J. (2003) Six degrees: The science of a connected age. W.W. Norton, New York/London
Watts D. J., Strogatz S. H. (1998) Collective dynamics of ‘small world’ networks. Nature 393: 440–442
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Posner, Z. Spatio-Cultural Evolution as Information Dynamics—Part II. Found Sci 17, 163–203 (2012). https://doi.org/10.1007/s10699-011-9231-1
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DOI: https://doi.org/10.1007/s10699-011-9231-1