Complexes

We apply measures of complexity, emergence, and self-organization to an urban traffic model for comparing a traditional traffic-light coordination method with a self-organizing method in two scenarios: cyclic boundaries and non-orientable boundaries. We show that the measures are useful to identify and characterize different dynamical phases. It becomes clear that different operation regimes are required for different traffic demands. Thus, not only is traffic a non-stationary problem, requiring controllers to adapt constantly; controllers must also change drastically the complexity of their behavior depending on the demand. Based on our measures and extending Ashby’s law of requisite variety, we can say that the self-organizing method achieves an adaptability level comparable to that of a living system. Zubillaga, Darío; Cruz, Geovany; Aguilar, Luis D.; Zapotécatl, Jorge; Fernández, Nelson; Aguilar, José; Rosenblueth, David A.; Gershenson, Carlos. 2014. "Measuring the Complexit...

Aphorisms collection at  http://turing.iimas.unam.mx/~cgg/aforismos.html “Reality: always one step ahead of my most imaginative sarcasms” “The more I travel, the more borders become artificial” *“In science, there are no finished problems, only narrow-minded scientists” “The fact that it has always been that way does not mean that it cannot change” “Since I am finite, I tend to be biased towards speaking only about those things which I have experience with.” “If I say: "I might be wrong", I cannot be wrong” *“If you do not have the right perspective to see the rainbow, it does not imply that the rainbow is not there.” *“One can warmonger interpreting a religious or a scientific text.  One can peacemonger interpreting a religious or a scientific text.  What is more important: the text or the purpose of the interpretation?” “It is difficult to gain new knowledge without first questioning current knowledge” “Remember that you are always setting an example. Do things as yo...

We compared entropy for texts written in natural languages (English, Spanish) and artificial languages (computer software) based on a simple expression for the entropy as a function of message length and specific word diversity. Code text written in artificial languages showed higher entropy than text of similar length expressed in natural languages. Spanish texts exhibit more symbolic diversity than English ones. Results showed that algorithms based on complexity measures differentiate artificial from natural languages, and that text analysis based on complexity measures allows the unveiling of important aspects of their nature. We propose specific expressions to examine entropy related aspects of tests and estimate the values of entropy, emergence, self-organization, and complexity based on specific diversity and message length. Complexity measurement of natural and artificial languages Gerardo Febres, Klaus Jaffé and Carlos Gershenson Complexity , Early View http://dx.doi.org/...