Some Analytical Properties of the Model for Stochastic Evolutionary Games in Finite Populations with Non-uniform Interaction Rate

Traditional evolutionary games assume uniform interaction rate, which means that the rate at which individuals meet and interact is independent of their strategies. But in some systems, especially biological systems, the players interact with each other discriminately. Taylor and Nowak (2006) were the first to establish the corresponding non-uniform interaction rate model by allowing the interaction rates to depend on strategies. Their model is based on replicator dynamics which assumes an infinite size population. But in reality, the number of individuals in the population is always finite, and there will be some random interference in the individuals' strategy selection process. Therefore, it is more practical to establish the corresponding stochastic evolutionary model in finite populations. In fact, the analysis of evolutionary games in a finite size population is more difficult. Just as Taylor and Nowak said in the outlook section of their paper, "The analysis of non-uniform interaction rates should be extended to stochastic game dynamics of finite populations." In this paper, we are exactly doing this work. We extend Taylor and Nowak's model from infinite to finite case, especially focusing on the influence of non-uniform connection characteristics on the evolutionary stable state of the system. We model the strategy evolutionary process of the population by a continuous ergodic Markov process. Based on the limit distribution of the process, we can give the evolutionary stable state of the system. We make a complete classification of the symmetric 2×2 games. For each case game, the corresponding limit distribution of the Markov-based process is given when noise intensity is small enough. In contrast with most literatures in evolutionary games using the simulation method, all our results obtained are analytical. Especially, in the dominant-case game, coexistence of the two strategies may become evolutionary stable states in our model. This result can be used to explain the emergence of cooperation in the Prisoner is Dilemma Games to some extent. Some specific examples are given to illustrate our results.     

Effects of migration on the evolutionary game dynamics in finite populations with community structures

We investigate the impacts of migration on the evolutionary game dynamics in finite populations with community structures in the framework of evolutionary game theory. In contrast to deterministic dynamics, our model incorporates stochastic factors induced by the finite population size. Based on the analysis of the stationary distribution of the evolutionary process in the limit of rare mutations, we prove that it is most likely to find the population in the community where all individuals have the lower migration rate. Furthermore, we show that reducing the difference between the migration rates of distinct communities can increase the first hitting time to the homogeneous absorbing state and can prolong the coexistence time of different species, promoting the conservation of biodiversity.     

Characteristic periodicities of collective behavior at the foreign exchange market

The Battle of the Sexes describes asymmetric conflicts in mating behavior of males and females. Males can be philanderer or faithful, while females are either fast or coy, leading to a cyclic dynamics. The adjusted replicator equation predicts stable coexistence of all four strategies. In this situation, we consider the effects of fluctuations stemming from a finite population size. We show that they unavoidably lead to extinction of two strategies in the population. However, the typical time until extinction occurs strongly prolongs with increasing system size. In the emerging time window, a quasi-stationary probability distribution forms that is anomalously flat in the vicinity of the coexistence state. This behavior originates in a vanishing linear deterministic drift near the fixed point. We provide numerical data as well as an analytical approach to the mean extinction time and the quasi-stationary probability distribution.     

Evolving complex food webs

We describe the properties of a model which links the ecology of food web structure with the evolutionary dynamics of speciation and extinction events; the model describes the dynamics of ecological communities on an evolutionary timescale. Species are defined as sets of characteristic features, and these features are used to determine interaction scores between species. A realistic population dynamics, which incorporates these scores, is used to determine the changes in population sizes on ecological time scales and so determine mean population sizes. We display typical examples of food webs constructed using the model and comment on the good agreement which is found between the model predictions and data on real webs.Received: 18 January 2004, Published online: 14 May 2004PACS: 87.23.Kg Dynamics of evolution - 87.23.Cc Population dynamics and ecological pattern formation - 89.75.Fb Structures and organization in complex systems     

Mutagenic evidence for the optimal control of evolutionary dynamics

Elucidating the fitness measures optimized during the evolution of complex biological systems is a major challenge in evolutionary theory. We present experimental evidence and an analytical framework demonstrating how biochemical networks exploit optimal control strategies in their evolutionary dynamics. Optimal control theory explains a striking pattern of extremization in the redox potentials of electron transport proteins, assuming only that their fitness measure is a control objective functional with bounded controls.     

Temporal behavior of evolutionary dynamics in finite dimensional population

We systematically study the temporal behavior of evolutionary dynamics in finite dimensional population based on evolutionary graph theory. Besides the spread of mutants, we also consider the spread of the impact of the initial mutant seed. The time-dependent behavior of these two spreading processes and their relationship are theoretically and computationally investigated. The ingredients and scaling behaviors of the interface between mutants and wild-type individuals are analyzed in detail, which have significant impact on temporal behavior of evolutionary dynamics. Since the evolutionary systems in nature are generally local and spatial, this research provides further understanding of temporal behavior in evolutionary dynamics at the theoretical level.     

The evolution of cooperation in public good game with deposit

The emergence of cooperation still remains a fundamental conundrum in the social and behavior sciences. We introduce a new mechanism, deposit mechanism, into theoretical model to explore how this mechanism promotes cooperation in a well-mixed population. Firstly, we extend the common binary-strategy combination of cooperation and defection in public good game by adding a third strategy, namely, deposit cooperation. The players with deposit cooperation strategy pay a deposit in advance to obtain the benefits of public good at a lower contributions compared with the players with cooperation strategy, when the provision of public good is successful. Then, we explore the evolution of cooperation in the public good game with deposit by means of the replicator dynamics. Theoretical computations and stimulations show that the deposit mechanism can promote cooperation in a well-mixed population, and the numbers of equilibrium point are determined by variables of public good game. On the one hand, when the coexistence of cooperators and defectors is the stable equilibrium point in the evolutionary system, increasing the threshold of public good and adopting the weak altruism way for share benefits can enhance the level of cooperation in the population. On the other hand, if the coexistence of deposit cooperators and defectors is the stable equilibrium point, it is effective to promote the deposit cooperation by lowering the values of discount and deposit, and raising the threshold of public good.     

Coexistence of cooperators and defectors in well mixed populations mediated by limiting resources

Traditionally, resource limitation in evolutionary game theory is assumed just to impose a constant population size. Here we show that resource limitations may generate dynamical payoffs able to alter an original prisoner's dilemma, and to allow for the stable coexistence between unconditional cooperators and defectors in well-mixed populations. This is a consequence of a self-organizing process that turns the interaction payoff matrix into evolutionary neutral, and represents a resource-based control mechanism preventing the spread of defectors. To our knowledge, this is the first example of coexistence in well-mixed populations with a game structure different from a snowdrift game.     

Modeling and analyzing of botnet interactions

The dynamics of interacting botnets and the effects of the strategies selected by interacting botnet owners on the spread of botnets remain unclear. As a result, in this paper, we present a botnet interaction model, obtained by coupling a fast evolutionary game dynamics to a slow population dynamics model, in which two botnet types are considered. We analyze the fast evolutionary game model and obtain two stable equilibria. Additionally, we substitute them into the complete model and get two reduced models. Such models allow us to study the effects of strategies selected by botnet owners. Analysis of the models shows that when all owners adopt the cooperative strategy both types of botnets can survive with much lower contact rates. However, while they choose the competitive strategy one type of botnet will become extinct and the other will persist with a lower infection rate. The equilibrium conditions of the evolutionary game model, which can guide us in designing effective counter-botnet methods, are also obtained.     

The Value of Information Searching against Fake News

Inspired by the Daley-Kendall and Goffman-Newill models, we propose an Ignorant-Believer-Unbeliever rumor (or fake news) spreading model with the following characteristics: (i) a network contact between individuals that determines the spread of rumors; (ii) the value (cost versus benefit) for individuals who search for truthful information (learning); (iii) an impact measure that assesses the risk of believing the rumor; (iv) an individual search strategy based on the probability that an individual searches for truthful information; (v) the population search strategy based on the proportion of individuals of the population who decide to search for truthful information; (vi) a payoff for the individuals that depends on the parameters of the model and the strategies of the individuals. Furthermore, we introduce evolutionary information search dynamics and study the dynamics of population search strategies. For each value of searching for information, we compute evolutionarily stable information (ESI) search strategies (occurring in non-cooperative environments), which are the attractors of the information search dynamics, and the optimal information (OI) search strategy (occurring in (eventually forced) cooperative environments) that maximizes the expected information payoff for the population. For rumors that are advantageous or harmful to the population (positive or negative impact), we show the existence of distinct scenarios that depend on the value of searching for truthful information. We fully discuss which evolutionarily stable information (ESI) search strategies and which optimal information (OI) search strategies eradicate (or not) the rumor and the corresponding expected payoffs. As a corollary of our results, a recommendation for legislators and policymakers who aim to eradicate harmful rumors is to make the search for truthful information free or rewarding.     

In search for the optimal strategy in population dynamics

A unification of recently proposed models describing population dynamics is presented. We study the effect of different factors, like environmental conditions, concentration of individuals in a given area and migration strategies, on population dynamics. Moreover, we show that a population occupying a smaller area is more susceptible to extinction, which is a well known biological fact. We solve the model using Monte Carlo simulations and the mean-field approach. Constructing flow diagrams we find the optimal strategy in population dynamics. Received 10 June 2001 and Received in final form 22 November 2001     

Evolutionary game theory in growing populations

Existing theoretical models of evolution focus on the relative fitness advantages of different mutants in a population while the dynamic behavior of the population size is mostly left unconsidered. We present here a generic stochastic model which combines the growth dynamics of the population and its internal evolution. Our model thereby accounts for the fact that both evolutionary and growth dynamics are based on individual reproduction events and hence are highly coupled and stochastic in nature. We exemplify our approach by studying the dilemma of cooperation in growing populations and show that genuinely stochastic events can ease the dilemma by leading to a transient but robust increase in cooperation.     

Eckhaus instability in systems with large delay

The dynamical behavior of various physical and biological systems under the influence of delayed feedback or coupling can be modeled by including terms with delayed arguments in the equations of motion. In particular, the case of long delay may lead to complicated and high-dimensional dynamics. We investigate the effects of delay in systems that display an oscillatory instability (Hopf bifurcation) in the absence of delay. We show by analytical and numerical methods that the dynamical scenario includes the coexistence of multiple stable periodic solutions and can be described in terms of the Eckhaus instability, which is well known in the context of spatially extended systems.     

Stochastic evolutionary public goods game with first and second order costly punishments in finite populations

We study the stochastic evolutionary public goods game with punishment in a finite size population. Two kinds of costly punishments are considered, i.e., first-order punishment in which only the defectors are punished, and second-order punishment in which both the defectors and the cooperators who do not punish the defective behaviors are punished. We focus on the stochastic stable equilibrium of the system. In the population, the evolutionary process of strategies is described as a finite state Markov process. The evolutionary equilibrium of the system and its stochastic stability are analyzed by the limit distribution of the Markov process. By numerical experiments, our findings are as follows.(i) The first-order costly punishment can change the evolutionary dynamics and equilibrium of the public goods game, and it can promote cooperation only when both the intensity of punishment and the return on investment parameters are large enough.(ii)Under the first-order punishment, the further imposition of the second-order punishment cannot change the evolutionary dynamics of the system dramatically, but can only change the probability of the system to select the equilibrium points in the "C+P" states, which refer to the co-existence states of cooperation and punishment. The second-order punishment has limited roles in promoting cooperation, except for some critical combinations of parameters.(iii) When the system chooses"C+P" states with probability one, the increase of the punishment probability under second-order punishment will further increase the proportion of the "P" strategy in the "C+P" states.     

Dynamical first-order phase transition in kinetically constrained models of glasses

We show that the dynamics of kinetically constrained models of glass formers takes place at a first-order coexistence line between active and inactive dynamical phases. We prove this by computing the large-deviation functions of suitable space-time observables, such as the number of configuration changes in a trajectory. We present analytic results for dynamic facilitated models in a mean-field approximation, and numerical results for the Fredrickson-Andersen model, the East model, and constrained lattice gases, in various dimensions. This dynamical first-order transition is generic in kinetically constrained models, and we expect it to be present in systems with fully jammed states.     

Global Migration Can Lead to Stronger Spatial Selection than Local Migration

The outcome of evolutionary processes depends on population structure. It is well known that mobility plays an important role in affecting evolutionary dynamics in group structured populations. But it is largely unknown whether global or local migration leads to stronger spatial selection and would therefore favor to a larger extent the evolution of cooperation. To address this issue, we quantify the impacts of these two migration patterns on the evolutionary competition of two strategies in a finite island model. Global migration means that individuals can migrate from any one island to any other island. Local migration means that individuals can only migrate between islands that are nearest neighbors; we study a simple geometry where islands are arranged on a one-dimensional, regular cycle. We derive general results for weak selection and large population size. Our key parameters are: the number of islands, the migration rate and the mutation rate. Surprisingly, our comparative analysis reveals that global migration can lead to stronger spatial selection than local migration for a wide range of parameter conditions. Our work provides useful insights into understanding how different mobility patterns affect evolutionary processes.     

Dynamical organization of cooperation in complex topologies

In this Letter, we study how cooperation is organized in complex topologies by analyzing the evolutionary (replicator) dynamics of the prisoner's dilemma, a two-player game with two available strategies, defection and cooperation, whose payoff matrix favors defection. We show that, asymptotically, the population is partitioned into three subsets: individuals that always cooperate (pure cooperators), always defect (pure defectors), and those that intermittently change their strategy. In fact, the size of the later set is the biggest for a wide range of the "stimulus to defect" parameter. While in homogeneous random graphs pure cooperators are grouped into several clusters, in heterogeneous scale-free (SF) networks they always form a single cluster containing the most connected individuals (hubs). Our results give further insights into why cooperation in SF networks is enhanced.     

Superheating and solid-liquid phase coexistence in nanoparticles with nonmelting surfaces

We present a phenomenological model of melting in nanoparticles with facets that are only partially wet by their liquid phase. We show that in this model, as the solid nanoparticle seeks to avoid coexistence with the liquid, the microcanonical melting temperature can exceed the bulk melting point and that the onset of coexistence is a first-order transition. We show that these results are consistent with molecular dynamics simulations of aluminum nanoparticles which remain solid above the bulk melting temperature.     

Manipulation with heterogeneity within a species population formulated as an inverse problem

Dependence of the evolutionary dynamics on the population’s heterogeneity has been reliably recognized and studied within the frame of evolutionary optimization theory. As the causal relation between the heterogeneity and dynamics of environment has been revealed, the possibility to influence convergence rate of evolutionary processes by purposeful manipulation with environment emerges.For the above purposes we formulate the task as the inverse problem meaning that desired population heterogeneity, quantified by Tsallis information entropy, represents the model’s input and dynamics of environment leading to desired population heterogeneity is looked for. Here the presented abstract model of evolutionary motion within the inverse model of replicating species is case-independent and it is relevant for the broad range of phenomena observed at cellular, ecological, economic and social scales. We envision relevance of the model for anticancer therapy, in which the effort is to circumvent heterogeneity as it typically correlates with the therapy efficiency.