The scales of a system’s behavior determine what it can do. By comparing these scales to the tasks for which the system is designed, we can see whether or not it can achieve its goals and why. Multiscale Analysis proves useful in the study of large organizations, such as healthcare, the military, and corporations.

Complex Systems Modeling

NECSI uses conceptual and mathematical models to characterize the multiscale complexity of mathematical, physical and social systems, and solve a mystery of complex systems: strong emergence.

The Limits of Phenomenology: From Behaviorism to Drug Testing and Engineering. Y. Bar-Yam (2013).

Information flow through a chaotic channel: prediction and postdiction at finite resolution, R. Metzler, Y. Bar-Yam, M. Kardar (2004).

Sensitivity of ballistic deposition to pseudorandom number generators, R. M. D'Souza, Y. Bar-Yam, M. Kardar (1998).

A Mathematical Theory of Strong Emergence using Multiscale Variety, Y. Bar-Yam (2004).

Computationally tractable pairwise complexity profile, Y. Bar-Yam, D. Harmon, Y. Bar-Yam (May, 2013).

Multiscale Representation Phase I, Report to Chief of Naval Operations Strategic Studies Group, Y. Bar-Yam, (2001).

Multiscale Variety in Complex Systems,Y. Bar-Yam (2004).

A self-stabilizing, robust region finder applied to color and optical flow pictures, M. Ben-Ezra, M. Werman, Y. Bar-Yam (May, 2001).


NECSI identifies the inherent limitations of traditional engineering for highly complex challenges, and shows the potential of an evolutionary approach.

About Engineering Complex Systems: Multiscale Analysis and Evolutionary Engineering, Y. Bar-Yam, in Engineering Self Organising Systems: Methodologies and Applications, S. Brueckner, G. Di Marzo Serugendo, A. Karageorgos, R. Nagpal Eds. (2005).

Large-Scale Engineering and Evolutionary Change, Useful Concepts for Implementation of FORCEnet Y. Bar-Yam (2002).


Generalizing our understanding of information to include scale provides an important tool for characterizing any system.

Multiscale complexity/entropy, Y. Bar-Yam (2004).

Sum rule for multiscale representations of Kinematic systems,Y. Bar-Yam (2002).

Multiscale analysis of information correlations in an infinite-range, ferromagnetic Ising system, S. Gheorghiu-Svirschevski, Y. Bar-Yam, Phys Rev E 70, 066115 (2004).

Multiscale complexity of correlated Gaussians, R. Metzler, Y. Bar-Yam (2005).

Social Systems

Models of human social interaction developed by NECSI provide insight on the future of human civilization as well as achieving individual well-being.

Environmental Complexity: Information For Human-Environment Well-being. Y. Bar-Yam, A. Davidson (1997).

Complexity Rising: From Human Beings to Human Civilization, a Complexity Profile, Y. Bar-Yam (2002).



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