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Zachar I.,Eotvos Lorand University | Fedor A.,Eotvos Lorand University | Szathmary E.,Eotvos Lorand University | Szathmary E.,Collegium Budapest Institute for Advanced Study
PLoS ONE | Year: 2011

The simulation of complex biochemical systems, consisting of intertwined subsystems, is a challenging task in computational biology. The complex biochemical organization of the cell is effectively modeled by the minimal cell model called chemoton, proposed by Gánti. Since the chemoton is a system consisting of a large but fixed number of interacting molecular species, it can effectively be implemented in a process algebra-based language such as the BlenX programming language. The stochastic model behaves comparably to previous continuous deterministic models of the chemoton. Additionally to the well-known chemoton, we also implemented an extended version with two competing template cycles. The new insight from our study is that the coupling of reactions in the chemoton ensures that these templates coexist providing an alternative solution to Eigen's paradox. Our technical innovation involves the introduction of a two-state switch to control cell growth and division, thus providing an example for hybrid methods in BlenX. Further developments to the BlenX language are suggested in the Appendix. © 2011 Zachar et al. Source

Mas M.,University of Groningen | Flache A.,University of Groningen | Helbing D.,ETH Zurich | Helbing D.,Santa Fe Institute | Helbing D.,Collegium Budapest Institute for Advanced Study
PLoS Computational Biology | Year: 2010

One of the most intriguing dynamics in biological systems is the emergence of clustering, in the sense that individuals selforganize into separate agglomerations in physical or behavioral space. Several theories have been developed to explain clustering in, for instance, multi-cellular organisms, ant colonies, bee hives, flocks of birds, schools of fish, and animal herds. A persistent puzzle, however, is the clustering of opinions in human populations, particularly when opinions vary continuously, such as the degree to which citizens are in favor of or against a vaccination program. Existing continuous opinion formation models predict "monoculture" in the long run, unless subsets of the population are perfectly separated from each other. Yet, social diversity is a robust empirical phenomenon, although perfect separation is hardly possible in an increasingly connected world. Considering randomness has not overcome the theoretical shortcomings so far. Small perturbations of individual opinions trigger social influence cascades that inevitably lead to monoculture, while larger noise disrupts opinion clusters and results in rampant individualism without any social structure. Our solution to the puzzle builds on recent empirical research, combining the integrative tendencies of social influence with the disintegrative effects of individualization. A key element of the new computational model is an adaptive kind of noise. We conduct computer simulation experiments demonstrating that with this kind of noise a third phase besides individualism and monoculture becomes possible, characterized by the formation of metastable clusters with diversity between and consensus within clusters. When clusters are small, individualization tendencies are too weak to prohibit a fusion of clusters. When clusters grow too large, however, individualization increases in strength, which promotes their splitting. In summary, the new model can explain cultural clustering in human societies. Strikingly, model predictions are not only robust to "noise"-randomness is actually the central mechanism that sustains pluralism and clustering. © 2010 Mäs et al. Source

Fernando C.,University of Sussex | Kampis G.,Eotvos Lorand University | Szathmary E.,Collegium Budapest Institute for Advanced Study
Procedia Computer Science | Year: 2011

Evolvability in its simplest form is the ability of a population to respond to directional selection. More interestingly it means that some lineages show open-ended evolution by accumulating novel adaptations, and that some lineages complexity can increase indefinitely. Unlimited heredity is a precondition for such rich open-endedness, another one seems to be (analogous to) chemical combinatorics. The richness of matter seems to be a source of challenges and opportunities not yet matched in artificial algorithms. However, some "artificial" systems can be more evolvable than natural ones because for the former the whole population is not under the constraint to survive in the wild. A form of artificial selection may happen even in the brain of replicable patterns that yield complex adaptations within the lifetime of the individual. © Selection and peer-review under responsibility of FET11 conference organizers and published by Elsevier B.V. Source

Helbing D.,ETH Zurich | Helbing D.,Santa Fe Institute | Helbing D.,Collegium Budapest Institute for Advanced Study | Szolnoki A.,Research Institute for Technical Physics and Materials Science | And 2 more authors.
New Journal of Physics | Year: 2010

We study the evolution of cooperation in spatial public goods games where, besides the classical strategies of cooperation (C) and defection (D), we consider punishing cooperators (PC) or punishing defectors (PD) as an additional strategy. Using a minimalist modeling approach, our goal is to separately clarify and identify the consequences of the two punishing strategies. Since punishment is costly, punishing strategies lose the evolutionary competition in case of well-mixed interactions. When spatial interactions are taken into account, however, the outcome can be strikingly different, and cooperation may spread. The underlying mechanism depends on the character of the punishment strategy. In the case of cooperating punishers, increasing the fine results in a rising cooperation level. In contrast, in the presence of the PD strategy, the phase diagram exhibits a reentrant transition as the fine is increased. Accordingly, the level of cooperation shows a non-monotonous dependence on the fine. Remarkably, punishing strategies can spread in both cases, but based on largely different mechanisms, which depend on the cooperativeness (or not) of punishers. © IOP Publishing Ltd and Deutsche Physikalische Gesellschaft. Source

Kesting A.,TU Dresden | Treiber M.,TU Dresden | Helbing D.,ETH Zurich | Helbing D.,Collegium Budapest Institute for Advanced Study
IEEE Transactions on Intelligent Transportation Systems | Year: 2010

Intervehicle communication (IVC) enables vehicles to exchange messages within a limited broadcast range and thus self-organize into dynamical vehicular ad hoc networks. For the foreseeable future, however, a direct connectivity between equipped vehicles in one direction is rarely possible. We therefore investigate an alternative mode in which messages are stored by relay vehicles traveling in the opposite direction and forwarded to vehicles in the original direction at a later time. The wireless communication consists of two transversal message hops across driving directions. Since direct connectivity for transversal hops and a successful message transmission to vehicles in the destination region are only a matter of time, the quality of this IVC strategy can be described in terms of the distribution function for the total transmission time. Assuming a Poissonian distance distribution between equipped vehicles, we derive analytical probability distributions for message transmission times and related propagation speeds for a deterministic and a stochastic model of the maximum range of direct communication. By means of integrated microscopic simulations of communication and bidirectional traffic flows, we validated the theoretical expectation for multilane roadways. We found little deviation of the analytical result for multilane scenarios but significant deviations for a single lane. This can be explained by vehicle platooning. We demonstrate the efficiency of the transverse hopping mechanism for a congestion-warning application in a microscopic traffic-simulation scenario. Messages are created on an event-driven basis by equipped vehicles getting into and out of a traffic jam. This application is operative for penetration levels as low as 1%. © 2010 IEEE. Source

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