abstract

Lattice-gas cellular automaton (LGCA) models are introduced as models for the analysis of pattern formation in interacting cell populations. LGCA models are cell-based, computationally efficient, and allow to integrate statistical and biophysical models for different levels of biological knowledge. Moreover, LGCA models permit multiscale analysis of collective phenomena emerging at multiple temporal and spatial scales.

abstract

We review recent numerical results on the role of talent and luck in getting success by means of a schematic agent-based model. In general, the role of luck is found to be very relevant in order to get success, while talent is necessary but not sufficient. Funding strategies to improve the success of the most talented people are also discussed.

abstract

Phylogeny is the field of modelling the temporal discrete dynamics of speciation. Complex models can nowadays be studied using the Approximate Bayesian Computation approach which avoids likelihood calculations. The field’s progression is hampered by the lack of robust software to estimate the numerous parameters of the speciation process. In this work, we present an R package, pcmabc, publicly available on CRAN, based on Approximate Bayesian Computations, that implements three novel phylogenetic algorithms for trait-dependent speciation modelling. Our phylogenetic comparative methodology takes into account both the simulated traits and phylogeny, attempting to estimate the parameters of the processes generating the phenotype and the trait. The user is not restricted to a predefined set of models and can specify a variety of evolutionary and branching models. We illustrate the software with a simulation-reestimation study focused around the branching Ornstein–Uhlenbeck process, where the branching rate depends non-linearly on the value of the driving Ornstein–Uhlenbeck process. Included in this work is a tutorial on how to use the software.

abstract

Although the digital piracy is believed to be a significant threat to the marketers of digital service products, there is a contradictory empirical evidence whether it is really the case. Nevertheless, a lot of effort from the industry and policy makers is put to attenuate that practice. Methods such as pricing strategies, education campaigns, legal regulations and prosecutions are typically used to decrease the tendency to pirate. Within this paper, we used a simple agent-based model to explore the role of the piracy on the digital goods market, as well as the impact of preventives and deterrents on the piracy itself. Our particular attention was paid to the e-book market, which has not been studied in the context of piracy so much yet. From our simulations, it follows that in the short term, some degree of the piracy may be beneficial for publishers of e-books, because it enhances the diffusion of a new title. In the long run, it is rather harmful for the publishers, because it usually forces the diffusion process to saturate at lower market penetration rates. We have also observed the ambiguous effect of piracy on the total welfare of the market participants. Moreover, we found that the final penetration rates of both the legal copy and the pirate one do not depend on the level of advertisement (including educational campaigns), but the advertisement significantly speeds up the process of adoption. The findings of the model can provide some hints for the publishers and policy makers as well as for the modelers aiming at more realistic models of digital markets.

abstract

While binary nearest-neighbour cellar automata (CA) have been studied in detail and from many different angles, the same cannot be said about ternary (three-state) CA rules. We present some results of our explorations of a small subset of the vast space of ternary rules, namely rules possessing additive invariants. We first enumerate rules with four different additive invariants, and then we investigate if any of them could be used to construct a two-rule solution of generalized density classification problem (DCP). We show that neither simple nor absolute classification is possible with a pair of ternary rules, where the first rule is all-conserving and the second one is reducible to two states. Similar negative result holds for another version of DCP we propose: symmetric interval-wise DCP. Finally, we show an example of a pair of rules which solve non-symmetric interval-wise DCP for initial configurations containing at least one zero.

abstract

Majority-vote model with independence is investigated on complex scale-free networks with degree distribution \(p_{k}\propto k^{\tilde {\gamma }}\). In the simplest version of the majority-vote model, the agents assume, with probability \(1- q\) (\(0 \lt q \lt 1/2\)), the opinion in agreement with that of the majority of their neighbors. In the majority-vote model with independence, the agents obey the above-mentioned update rule with probability \(1- \tilde {p}\) (\(0\lt \tilde {p}\lt 1\)), while with probability \(\tilde {p}\), they make decision randomly. It is shown that the parameters \(q\) and \(p=\tilde {p}/2\) are equivalent, and as one of them is decreased, with the other fixed, for \(\tilde {\gamma }\gt 5/2\), the model can exhibit transition to the ferromagnetic state at a critical value \(q_{\mathrm {c}}\) or \(p_{\mathrm {c}}\) which depends on the degree distribution. Critical behavior of the magnetization is determined in the heterogeneous mean-field approximation. For \(5/2\lt \tilde {\gamma } \lt 7/2\), this behavior is non-universal, with the magnetization scaling as \(M\propto ( q_{\mathrm {c}}-q)^{\beta }\) or \(M\propto ( p_{\mathrm {c}}-p)^{\beta }\) with \(\beta = 1/[2(\tilde {\gamma }-5/2)]\), and for \(\tilde {\gamma }\ge 7/2\), it becomes universal with \(\beta =1/2\). These results are confirmed by Monte Carlo simulations and finite size scaling analysis.

abstract

The functional anatomy between the human right atrium and the sinoatrial node (SAN) still remains an open problem under investigation. There are contradictory hypotheses of how the SAN is electrically connected to the atria. We use an accurate and efficient approach of the so-called hybrid automata to investigate electrophysiological aspects of the atria–SAN coupling. This approach allows us to simulate the tissue heterogeneity preserving high accuracy of cellular dynamics as a continuous time Markov process with transitions representing short-lived transient behaviors. Our simulations suggest that there is an optimal organization of the SAN exit pathways to the atrium, which here we have identified to be smaller than 1/4 (with maximum at 1/16) of all possible SAN exits to the atrium. At this fraction, the system provides almost always normal heart rhythm, if only the density of connections between cells is high enough and the cells perform the excitation with high probability. Deviations from these conditions could result in tachycardia or in a loss of rhythm.

abstract

The cellular automaton (CA) pulsing model described the surprising phenomenon of spontaneous, sustained and robust rhythmic oscillations, pulsing dynamics, when random wiring is applied to a 2d “glider rule” running in a 3-value totalistic CA. Case studies, pulsing measures, possible mechanisms, and implications for oscillatory networks in biology were presented. In this paper, we summarise the results, extend the entropy-density and density-return map plots to include a linked history, look at totalistic glider rules with neighbourhoods of 3, 4 and 5, as well as 6 and 7 studied previously, introduce methods to automatically recognise the wave-length, and extend results for randomly asynchronous updating. We show how the model is implemented in DDLab to validate results, output data, and allow experiments and research by others.