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Sandro M. Reia

Publications and source records attributed to Sandro M. Reia.

21 records · Page 2Linked to original sources

Effect of long-range interactions on the phase transition of Axelrod's model

Axelrod's model with $F=2$ cultural features, where each feature can assume $k$ states drawn from a Poisson distribution of parameter $q$, exhibits a continuous nonequilibrium phase transition in the square lattice. Here we use extensive Monte Carlo simulations and finite size scaling to study the critical behavior of the order parameter $ρ$, which is the fraction of sites that belong to the largest domain of an absorbing configuration averaged over many runs. We find that it vanishes as $ρ\sim \left (q_c^0 - q \right)^β$ with $β\approx 0.25$ at the critical point $q_c^0 \approx 3.10$ and that the exponent that measures the width of the critical region is $ν^0 \approx 2.1$. In addition, we find that introduction of long-range links by rewiring the nearest-neighbors links of the square lattice with probability $p$ turns the transition discontinuous, with the critical point $q_c^p$ increasing from $3.1$ to $27.17$, approximately, as $p$ increases from $0$ to $1$. The sharpness of the threshold, as measured by the exponent $ν^p \approx 1$ for $p>0$, increases with the square root of the number of nodes of the resulting small-world network.

cond-mat.stat-mech↗

Effect of group organization on the performance of cooperative processes

Problem-solving competence at group level is influenced by the structure of the social networks and so it may shed light on the organization patterns of gregarious animals. Here we use an agent-based model to investigate whether the ubiquity of hierarchical networks in nature could be explained as the result of a selection pressure favoring problem-solving efficiency. The task of the agents is to find the global maxima of NK fitness landscapes and the agents cooperate by broadcasting messages informing on their fitness to the group. This information is then used to imitate, with a certain probability, the fittest agent in their influence networks. For rugged landscapes, we find that the modular organization of the hierarchical network with its high degree of clustering eases the escape from the local maxima, resulting in a superior performance as compared with the scale-free and the random networks. The optimal performance in a rugged landscape is achieved by letting the main hub to be only slightly more propense to imitate the other agents than vice versa. The performance is greatly harmed when the main hub carries out the search independently of the rest of the group as well as when it compulsively imitates the other agents.

cs.SI↗

Nonsynchronous updating in the multiverse of cellular automata

In this paper we study updating effects on cellular automata rule space. We consider a subset of 6144 order-3 automata from the space of 262144 bi-dimensional outer-totalistic rules. We compare synchronous to asynchronous and sequential updatings. Focusing on two automata, we discuss how update changes destroy typical structures of these rules. Besides, we show that the first-order phase-transition in the multiverse of synchronous cellular automata, revealed with the use of a recently introduced control parameter, seems to be robust not only to changes in update schema but also to different initial densities.

nlin.CG↗