arXiv subjects
Publications and source records attributed to A. O. Sousa.
The standard Penna ageing model with sexual reproduction is enlarged by adding additional bit-strings for love: Marriage happens only if the male love strings are sufficiently different from the female ones. We simulate at what level of required difference the population dies out.
Through Monte Carlo Simulation, the well-known majority-vote model has been studied with noise on directed random graphs. In order to characterize completely the observed order-disorder phase transition, the critical noise parameter $q_c$, as well as the critical exponents $beta/nu$, $gamma/nu$ and $1/nu$ have been calculated as a function of the connectivity $z$ of the random graph.
We model formation and evolution of transverse dune fields. In the model, only the cross section of the dune is simulated. The only physical variable of relevance is the dune height, from which the dune width and velocity are determined, as well as phenomenological rules for interaction between two dunes of different heights. We find that dune fields with no sand on the ground between dunes are unstable, i.e. small dunes leave the higher ones behind. We then introduce a saturation length to simulate transverse dunes on a sand bed and show that this leads to stable dune fields with regular spacing and dune heights. Finally, we show that our model can be used to simulate coastal dune fields if a constant sand influx is considered, where the dune height increases with the distance from the beach, reaching a constant value.
The language competition model of Viviane de Oliveira et al is modified by associating with each language a string of 32 bits. Whenever a language changes in this Viviane model, also one randomly selected bit is flipped. If then only languages with different bit-strings are counted as different, the resulting size distribution of languages agrees with the empirically observed slightly asymmetric log-normal distribution. Several other modifications were also tried but either had more free parameters or agreed less well with reality.
We analyze the Sznajd opinion formation model, where a pair of neighboring individuals sharing the same opinion on a square lattice convince its six neighbors to adopt their opinions, when a fraction of the individuals is updated according to the usual random sequential updating rule (asynchronous updating), and the other fraction, the simultaneous updating (synchronous updating). This combined updating scheme provides that the bigger the synchronous frequency becomes, the more difficult the system reaches a consensus. Moreover, in the thermodynamic limit, the system needs only a small fraction of individuals following a different kind of updating rules to present a non-consensus state as a final state.
We present a renormalization approach to solve the Sznajd opinion formation model on complex networks. For the case of two opinions, we present an expression of the probability of reaching consensus for a given opinion as a function of the initial fraction of agents with that opinion. The calculations reproduce the sharp transition of the model on a fixed network, as well as the recently observed smooth function for the model when simulated on a growing complex networks.
Parapatric speciation is studied using an individual--based model with sexual reproduction. We combine the theory of mutation accumulation for biological ageing with an environmental selection pressure that varies according to the individuals geographical positions and phenotypic traits. Fluctuations and genetic diversity of large populations are crucial ingredients to model the features of evolutionary branching and are intrinsic properties of the model. Its implementation on a spatial lattice gives interesting insights into the population dynamics of speciation on a geographical landscape and the disruptive selection that leads to the divergence of phenotypes. Our results suggest that assortative mating is not an obligatory ingredient to obtain speciation in large populations at low gene flow.
A simple model of opinion formation dynamics in which binary-state agents make up their opinions due to the influence of agents in a local neighborhood is studied using different network topologies. Each agent uses two different strategies, the Sznajd rule with a probability $q$ and the Galam majority rule (without inertia) otherwise; being $q$ a parameter of the system. Initially, the binary-state agents may have opinions (at random) against or in favor about a certain topic. The time evolution of the system is studied using different network topologies, starting from different initial opinion densities. A transition from consensus in one opinion to the other is found at the same percentage of initial distribution no matter which type of network is used or which opinion formation rule is used.
Galam reshuffling introduced in opinion dynamics models is investigated under the nearest neighbor Ising model on a square lattice using Monte Carlo simulations. While the corresponding Galam analytical critical temperature T_C \approx 3.09 [J/k_B] is recovered almost exactly, it is proved to be different from both values, not reshuffled (T_C=2/arcsinh(1) \approx 2.27 [J/k_B]) and mean-field (T_C=4 [J/k_B]). On this basis, gradual reshuffling is studied as function of 0 \leq p \leq 1 where p measures the probability of spin reshuffling after each Monte Carlo step. The variation of T_C as function of p is obtained and exhibits a non-linear behavior. The simplest Solomon network realization is noted to reproduce Galam p=1 result. Similarly to the critical temperature, critical exponents are found to differ from both, the classical Ising case and the mean-field values.
We analyze the evolution of Sznajd Model with synchronous updating in several complex networks. Similar to the model on square lattice, we have found a transition between the state with no-consensus and the state with complete consensus in several complex networks. Furthermore, by adjusting the network parameters, we find that a large clustering coefficient favors development of a consensus. In particular, in the limit of large system size with the initial concentration p=0.5 of opinion +1, a consensus seems to be never reached for the Watts-Strogatz small-world network, when we fix the connectivity k and the rewiring probability p_s; nor for the scale-free network, when we fix the minimum node degree m and the triad formation step probability p_t.
A Bounded Confidence (BC) model of socio-physics, in which the agents have continuous opinions and can influence each other only if the distance between their opinions is below a threshold, is simulated on a still growing scale-free network considering several different strategies: for each new node (or vertex), that is added to the network all individuals of the network have their opinions updated following a BC model recipe. The results obtained are compared with the original model, with numerical simulations on different graph structures and also when it is considered on the usual fixed BA network. In particular, the comparison with the latter leads us to conclude that it does not matter much whether the network is still growing or is fixed during the opinion dynamics.
Several cases of the Sznajd model of socio-physics, that only a group of people sharing the same opinion can convince their neighbors, have been simulated on a more realistic network with a stronger clustering. In addition, many opinions, instead of usually only two, and a convincing probability have been also considered. Finally, with minor changes we obtain a vote distribution in good agreement with reality.
A square lattice is introduced into the Penna model for biological aging in order to study the evolution of diploid sexual populations under certain conditions when one single locus in the individual's genome is considered as identifier of species. The simulation results show, after several generations, the flourishing and coexistence of two separate species in the same environment, i.e., one original species splits up into two on the same territory (sympatric speciation). As well, the mortalities obtained are in a good agreement with the Gompertz law of exponential increase of mortality with age.
The consensus model of Deffuant et al is simplified by allowing for many discrete instead of infinitely many continuous opinions, on a directed Barabasi-Albert network. A simple scaling law is observed. We then introduce noise and also use a more realistic network and compare the results. Finally, we look at a multi-layer model representing various age levels, and we include advertising effects.
The Sznajd model of socio-physics, that only a group of people sharing the same opinion can convince their neighbors, is applied to a scale-free random network modeled by a deterministic graph. We also study a model for elections based on the Sznajd model and the exponent obtained for the distribution of votes during the transient agrees with those obtained for real elections in Brazil and India. Our results are compared to those obtained using a Barabasi-Albert scale-free network.
Why sex evolved and it prevails in nature remains one of the great puzzles of evolution. Most biologists would explain that it promotes genetic variability, however this explanation suffers from several difficulties. What advantages might sex confer? The present communication aims at certain investigations related to this question, in this way we introduce sexual recombination on the Hötzel model (with males and females) and we compare these results with those from asexual reproduction without recombination.
We modify the Penna Model for biological aging, which is based on the mutation-accumulation theory, in order to verify if there would be any evolutionary advantage of triploid over diploid organisms. We show that this is not the case, and that usual sex is always better than that involving three individuals.
Using a simple computer model for evolution, we show that in a sexual population subject only to age-increasing reproductive risk, a cessation of female reproduction emerges.