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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.

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.
PLoS Computational Biology | Year: 2010

Situations where individuals have to contribute to joint efforts or share scarce resources are ubiquitous. Yet, without proper mechanisms to ensure cooperation, the evolutionary pressure to maximize individual success tends to create a tragedy of the commons (such as over-fishing or the destruction of our environment). This contribution addresses a number of related puzzles of human behavior with an evolutionary game theoretical approach as it has been successfully used to explain the behavior of other biological species many times, from bacteria to vertebrates. Our agent-based model distinguishes individuals applying four different behavioral strategies: non-cooperative individuals ("defectors"), cooperative individuals abstaining from punishment efforts (called "cooperators" or "second-order free-riders"), cooperators who punish noncooperative behavior ("moralists"), and defectors, who punish other defectors despite being non-cooperative themselves ("immoralists"). By considering spatial interactions with neighboring individuals, our model reveals several interesting effects: First, moralists can fully eliminate cooperators. This spreading of punishing behavior requires a segregation of behavioral strategies and solves the "second-order free-rider problem". Second, the system behavior changes its character significantly even after very long times ("who laughs last laughs best effect"). Third, the presence of a number of defectors can largely accelerate the victory of moralists over non-punishing cooperators. Fourth, in order to succeed, moralists may profit from immoralists in a way that appears like an "unholy collaboration". Our findings suggest that the consideration of punishment strategies allows one to understand the establishment and spreading of "moral behavior" by means of gametheoretical concepts. This demonstrates that quantitative biological modeling approaches are powerful even in domains that have been addressed with non-mathematical concepts so far. The complex dynamics of certain social behaviors become understandable as the result of an evolutionary competition between different behavioral strategies. © 2010 Helbing et al.

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.

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.
Physical Review E - Statistical, Nonlinear, and Soft Matter Physics | Year: 2010

We study the evolution of cooperation in spatial public goods games with four competing strategies: cooperators, defectors, punishing cooperators, and punishing defectors. To explore the robustness of the cooperation-promoting effect of costly punishment, besides the usual strategy adoption dynamics we also apply strategy mutations. As expected, frequent mutations create kind of well-mixed conditions, which support the spreading of defectors. However, when the mutation rate is small, the final stationary state does not significantly differ from the state of the mutation-free model, independently of the values of the punishment fine and cost. Nevertheless, the mutation rate affects the relaxation dynamics. Rare mutations can largely accelerate the spreading of costly punishment. This is due to the fact that the presence of defectors breaks the balance of power between both cooperative strategies, which leads to a different kind of dynamics. © 2010 The American Physical Society.

Fernando C.,University of Sussex | Kampis G.,Eötvös Loránd 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.

Rodin A.S.,University of Houston | Rodin A.S.,Collegium Budapest Institute for Advanced Study | Szathmary E.,Collegium Budapest Institute for Advanced Study | Szathmary E.,Parmenides Center for the Study of Thinking | And 3 more authors.
Biology Direct | Year: 2011

Background: Synthesis of proteins is based on the genetic code - a nearly universal assignment of codons to amino acids (aas). A major challenge to the understanding of the origins of this assignment is the archetypal "key-lock vs. frozen accident" dilemma. Here we re-examine this dilemma in light of 1) the fundamental veto on "foresight evolution", 2) modular structures of tRNAs and aminoacyl-tRNA synthetases, and 3) the updated library of aa-binding sites in RNA aptamers successfully selected in vitro for eight amino acids.Results: The aa-binding sites of arginine, isoleucine and tyrosine contain both their cognate triplets, anticodons and codons. We have noticed that these cases might be associated with palindrome-dinucleotides. For example, one-base shift to the left brings arginine codons CGN, with CG at 1-2 positions, to the respective anticodons NCG, with CG at 2-3 positions. Formally, the concomitant presence of codons and anticodons is also expected in the reverse situation, with codons containing palindrome-dinucleotides at their 2-3 positions, and anticodons exhibiting them at 1-2 positions. A closer analysis reveals that, surprisingly, RNA binding sites for Arg, Ile and Tyr "prefer" (exactly as in the actual genetic code) the anticodon(2-3)/codon(1-2) tetramers to their anticodon(1-2)/codon(2-3) counterparts, despite the seemingly perfect symmetry of the latter. However, since in vitro selection of aa-specific RNA aptamers apparently had nothing to do with translation, this striking preference provides a new strong support to the notion of the genetic code emerging before translation, in response to catalytic (and possibly other) needs of ancient RNA life. Consistently with the pre-translation origin of the code, we propose here a new model of tRNA origin by the gradual, Fibonacci process-like, elongation of a tRNA molecule from a primordial coding triplet and 5'DCCA3' quadruplet (D is a base-determinator) to the eventual 76 base-long cloverleaf-shaped molecule.Conclusion: Taken together, our findings necessarily imply that primordial tRNAs, tRNA aminoacylating ribozymes, and (later) the translation machinery in general have been co-evolving to ''fit'' the (likely already defined) genetic code, rather than the opposite way around. Coding triplets in this primal pre-translational code were likely similar to the anticodons, with second and third nucleotides being more important than the less specific first one. Later, when the code was expanding in co-evolution with the translation apparatus, the importance of 2-3 nucleotides of coding triplets "transferred" to the 1-2 nucleotides of their complements, thus distinguishing anticodons from codons. This evolutionary primacy of anticodons in genetic coding makes the hypothesis of primal stereo-chemical affinity between amino acids and cognate triplets, the hypothesis of coding coenzyme handles for amino acids, the hypothesis of tRNA-like genomic 3' tags suggesting that tRNAs originated in replication, and the hypothesis of ancient ribozymes-mediated operational code of tRNA aminoacylation not mutually contradicting but rather co-existing in harmony.Reviewers: This article was reviewed by Eugene V. Koonin, Wentao Ma (nominated by Juergen Brosius) and Anthony Poole. © 2011 Rodin et al; licensee BioMed Central Ltd.

Zachar I.,Eötvös Loránd University | Fedor A.,Eötvös Loránd University | Szathmary E.,Eötvös Loránd University | Szathmary E.,Collegium Budapest Institute for Advanced Study | Szathmary E.,Parmenides Foundation
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.

Helbing D.,ETH Zurich | Helbing D.,Santa Fe Institute | Helbing D.,Collegium Budapest Institute for Advanced Study | Johansson A.,ETH Zurich | Johansson A.,University College London
PLoS ONE | Year: 2010

Background: Cooperation is of utmost importance to society as a whole, but is often challenged by individual self-interests. While game theory has studied this problem extensively, there is little work on interactions within and across groups with different preferences or beliefs. Yet, people from different social or cultural backgrounds often meet and interact. This can yield conflict, since behavior that is considered cooperative by one population might be perceived as non-cooperative from the viewpoint of another. Methodology and Principal Findings: To understand the dynamics and outcome of the competitive interactions within and between groups, we study game-dynamical replicator equations for multiple populations with incompatible interests and different power (be this due to different population sizes, material resources, social capital, or other factors). These equations allow us to address various important questions: For example, can cooperation in the prisoner's dilemma be promoted, when two interacting groups have different preferences? Under what conditions can costly punishment, or other mechanisms, foster the evolution of norms? When does cooperation fail, leading to antagonistic behavior, conflict, or even revolutions? And what incentives are needed to reach peaceful agreements between groups with conflicting interests? Conclusions and Significance: Our detailed quantitative analysis reveals a large variety of interesting results, which are relevant for society, law and economics, and have implications for the evolution of language and culture as well. © 2010 Helbing, Johansson.

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.

Helbing D.,ETH Zurich | Helbing D.,Santa Fe Institute | Helbing D.,Collegium Budapest Institute for Advanced Study | Johansson A.,ETH Zurich
Physical Review E - Statistical, Nonlinear, and Soft Matter Physics | Year: 2010

Evolutionary game theory has been successfully used to investigate the dynamics of systems, in which many entities have competitive interactions. From a physics point of view, it is interesting to study conditions under which a coordination or cooperation of interacting entities will occur, be it spins, particles, bacteria, animals, or humans. Here, we analyze the case, where the entities are heterogeneous, particularly the case of two populations with conflicting interactions and two possible states. For such systems, explicit mathematical formulas will be determined for the stationary solutions and the associated eigenvalues, which determine their stability. In this way, four different types of system dynamics can be classified and the various kinds of phase transitions between them will be discussed. While these results are interesting from a physics point of view, they are also relevant for social, economic, and biological systems, as they allow one to understand conditions for (1) the breakdown of cooperation, (2) the coexistence of different behaviors ("subcultures"), (3) the evolution of commonly shared behaviors ("norms"), and (4) the occurrence of polarization or conflict. We point out that norms have a similar function in social systems that forces have in physics. © 2010 The American Physical Society.

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