Dynamical reconstruction of complex systems

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(CAREFUL WITH THIS LINK: IT MIGHT NOT OPEN) Bottom-up scientific field detection for dynamical and hierarchical science mapping, methodology and case study David Chavalarias and Jean-Philippe Cointet To appear in Scientometrics Vol. 75 No. 1 , (DOI): 10.1007/s11192-007-1825-6

Co-evolution in Epistemic Networks -- Reconstructing Social Complex Systems Camille Roth Structure and Dynamics: eJournal of Anthropological and Related Sciences 1#3

Technology and Culture: The Dissemination and the Potential 'Lock-in' of New Technologies Loet Leydesdorff (2001) Journal of Artificial Societies and Social Simulation vol. 4, no. 3.

Reconstruction failure: questioning level design Camille Roth, EPOS II — 2nd Workshop on Epistemological Perspectives On Simulation, October 5–6, 2006 — Brescia, Italy Abstract

[http://scitation.aip.org/getabs/servlet/GetabsServlet?prog=normal&id=CHAOEH000017000001013110000001&idtype=cvips&gifs=Yes A unified approach to attractor reconstruction] Chaos 17, 013110 (2007) (9 pages) Issue Date: March 2007 Louis M. Pecora, Linda Moniz, Jonathan Nichols

Abstract: In the analysis of complex, nonlinear time series, scientists in a variety of disciplines have relied on a time delayed embedding of their data, i.e., attractor reconstruction. The process has focused primarily on intuitive, heuristic, and empirical arguments for selection of the key embedding parameters, delay and embedding dimension. This approach has left several longstanding, but common problems unresolved in which the standard approaches produce inferior results or give no guidance at all. We view the current reconstruction process as unnecessarily broken into separate problems. We propose an alternative approach that views the problem of choosing all embedding parameters as being one and the same problem addressable using a single statistical test formulated directly from the reconstruction theorems. This allows for varying time delays appropriate to the data and simultaneously helps decide on embedding dimension. A second new statistic, undersampling, acts as a check against overly long time delays and overly large embedding dimension. Our approach is more flexible than those currently used, but is more directly connected with the mathematical requirements of embedding. In addition, the statistics developed guide the user by allowing optimization and warning when embedding parameters are chosen beyond what the data can support. We demonstrate our approach on uni- and multivariate data, data possessing multiple time scales, and chaotic data. This unified approach resolves all the main issues in attractor reconstruction. ©2007 American Institute of Physics

Dont know if this is of interest: Klüver, J., 1996: Sociological Discourses in Virtual Reality. A Hybrid System for the Reconstruction and Comparision of Sociological Theories. In: Social Science Computer Review 14, 280 - 292.

Dont know if this is of interest: Socionics: Sociological Concepts for Social Systems of Artificial (and Human) Agents Thomas Malsch and Ingo Schulz-Schaeffer (2007) Journal of Artificial Societies and Social Simulation vol. 10, no. 1