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In a recent study, Ohira and Sawatari presented a simple model of computer network traac dynamics. These authors showed that a phase transition point is present separating the low-traac phase with no congestion from the congestion phase as the packet creation rate increases. We further investigated this model by relaxing the network topology using a random(More)
A new model ecosystem of many interacting species is introduced in which the species are connected through a random matrix with a given connectivity. The model is studied both analytically and by numerical simulations. A probability distribution derived from the model is in good agreement with simulations and ÿeld data. It is also shown that the(More)
A new order parameter approximation to random boolean networks (RBN) is introduced, based on the concept of Boolean derivative. A statistical argument involving an annealed approximation is used, allowing to measure the order parameter in terms of the statistical properties of a random matrix. Using the same formalism, a Lyapunov exponent is calculated,(More)
Urban centers present all over the world striking similarities which translate into universal laws describing their growth and morphology. In this paper, we study a simple 2-dimensional cellular automata model containing what we identify as essential ingredients in the demographic change. The slow addition of population to an initially empty area (mimicking(More)
Many natural systems, as social insects, perform complex computations collectively. In these groups, large numbers of individuals communicate in a local way and send information to its nearest neighbors. Interestingly, a general observation of these societies reveals that the computational capabilities of individuals are fairly limited, suggesting that the(More)
A new order parameter approximation to Random Boolean Networks (RBN) is introduced, based on the concept of Boolean derivative. A statistical argument involving an annealed approximation is used, allowing to measure the order parameter in terms of the statistical properties of a random matrix. Using the same formalism, a Lyapunov exponent is calculated,(More)
We describe a method to discriminate between ordered and turbulent behavior in a general class of collective systems known as Globally Coupled Maps (GCM). Our method is able to discover an unknown small ordered region inside the turbulent phase of GCM parameter space. The computational nature of the method is the main novelty of our approach; it is another(More)
We suggest that the interaction of a Globally Coupled Map (GCM) with an individual element inside the system is, from a computational point of view, indistinguishable of a (,)-dependent noise in the turbulent region of the phase space. Therefore, we can use the framework of Computational Mechanics to give a measure that clearly separates the ordered from(More)