Effects of Inertia on Evolutionary Prisoner's Dilemma Game

Considering the inertia of individuals in real life, we propose a modified Fermi updating rule, where the inertia of players is introduced into evolutionary prisoner's dilemma game (PDG) on square lattices. We mainly focus on how the inertia affects the cooperative behavior of the system. Interestingly, we find that the cooperation level has a nonmonotonic dependence on the inertia: with small inertia, cooperators will soon be invaded by defectors; with large inertia, players are unwilling to change their strategies and the cooperation level remains the same as the initial state; while a moderate inertia can induce the highest cooperation level. Moreover, effects of environmental noise and individual inertia are studied. Our work may be helpful in understanding the emergence and persistence of cooperation in nature and society.     

Behavior of Collective Cooperation Yielded by Two Update Rules in Social Dilemmas: Combining Fermi and Moran Rules

We combine the Fermi and Moran update rules in the spatial prisoner's dilemma and snowdrift games to investigate the behavior of collective cooperation among agents on the regular lattice. Large-scale simulations indicate that, compared to the model with only one update rule, the cooperation behavior exhibits the richer phenomena, and the role of update dynamics should be paid more attention in the evolutionary game theory. Meanwhile, we also observe that the introduction of Moran rule, which needs to consider all neighbor's information, can markedly promote the aggregate cooperation level, that is, randomly selecting the neighbor proportional to its payoff to imitate will facilitate the cooperation among agents. Current results will contribute to further understand the cooperation dynamics and evolutionary behaviors within many biological, economic and social systems.     

Modelling a social dilemma of mode choice based on commuters’ expectations and social learning

This study attempts to apply an agent-based approach to modelling a social dilemma of travel mode choice considering psychological and sociological aspects. A traveller is modelled to have expectations, which shows the traveller’s beliefs about the influence of other group members on his action, as decision-making rules. Social interaction using a group-based interaction is hypothesized to be important. We apply an imitation game based on social learning mechanisms to the model. Two kinds of mechanism are used: payoff-biased and conformist transmission. The model reveals the conditions that make cooperation as a possible outcome are optimistic bandwagon expectations, group-based interactions, and strong conformist transmissions.     

Cooperative Dynamics in Lattice-Embedded Scale-Free Networks

We investigate cooperative behaviors of lattice-embedded scale-free networking agents in the prisoner＇s dilemma game model by employing two initial strategy distribution mechanisms, which are specific distribution to the most connected sites （hubs） and random distribution. Our study indicates that the game dynamics crucially depends on the underlying spatial network structure with different strategy distribution mechanism. The cooperators＇ specific distribution contributes to an enhanced level of cooperation in the system compared with random one, and cooperation is robust to cooperators＇ specific distribution but fragile to defectors＇ specific distribution. Especially, unlike the specific case, increasing heterogeneity of network does not always favor the emergence of cooperation under random mechanism. Furthermore, we study the geographical effects and find that the graphically constrained network structure tends to improve the evolution of cooperation in random case and in specific one for a large temptation to defect.     

Explaining cooperation in the finitely repeated simultaneous and sequential prisoner’s dilemma game under incomplete and complete information

Explaining cooperation in social dilemmas is a central issue in behavioral science, and the prisoner’s dilemma (PD) is the most frequently employed model. Theories assuming rationality and selfishness predict no cooperation in PDs of finite duration, but cooperation is frequently observed. We therefore build a model of how individuals in a finitely repeated PD with incomplete information about their partner’s preference for mutual cooperation decide about cooperation. We study cooperation in simultaneous and sequential PDs. Our model explains three behavioral regularities found in the literature: (i) the frequent cooperation in one-shot and finitely repeated N-shot games, (ii) cooperation rates declining over the course of the game, and (iii) cooperation being more frequent in the sequential PD than in the simultaneous PD.     

Preplay negotiations and the prisoner's dilemma

In order to improve outcomes of one shot noncooperative games a formal procedure for conducting preplay negotiations is proposed. For the prisoners' dilemma game it is shown that all the perfect equilibrium in the induced game (the game with the preplays) yield the cooperative pay-off. For another game it is shown that all perfect equilibrium payoffs converge to be Pareto optimal as the number of preplays increases.     

Evolutionary prisoner’s dilemma game on highly clustered community networks

This paper studies the evolutionary prisoner's dilemma game on a highly clustered community network in which the clustering coefficient and the community size can be tuned. It finds that the clustering coefficient in such a degree-homogeneous network inhibits the emergence of cooperation for the entire range of the payoff parameter. Moreover, it finds that the community size can also have a marked influence on the evolution of cooperation, with a larger community size leading to not only a lower cooperation level but also a smaller threshold of the payoff parameter above which cooperators become extinct.     

Rational behavior is a ‘double-edged sword’ when considering voluntary vaccination

Of particular importance for public health is how to understand strategic vaccination behavior in social networks. Social learning is a central aspect of human behavior, and it thus shapes vaccination individuals’ decision-making. Here, we study two simple models to address the impact of the more rational decision-making of individuals on voluntary vaccination. In the first model, individuals are endowed with memory capacity for their past experiences of dealing with vaccination. In addition to their current payoffs, they also take account of the historical payoffs that are discounted by a memory-decaying factor. They use such overall payoffs (weighing the current payoffs and historical payoffs) to reassess their vaccination strategies. Those who have higher overall payoffs are more likely imitated by their social neighbors. In the second model, individuals do not blindly learn the strategies of neighbors; they also combine the fraction of infection in the past epidemic season. If the fraction of infection surpasses the perceived risk threshold, individuals will increase the probability of taking vaccination. Otherwise, they will decrease the probability of taking vaccination. Then we use evolutionary game theory to study the vaccination behavior of people during an epidemiological process. To do this, we propose a two-stage model: individuals make vaccination decisions during a yearly vaccination campaign, followed by an epidemic season. This forms a feedback loop between the vaccination decisions of individuals and their health outcomes, and thus payoffs. We find that the two more rational decision-making models have nontrivial impacts on the vaccination behavior of individuals, and, as a result, on the final fraction of infection. Our results highlight that, from an individual’s viewpoint, the decisions are optimal and more rational. However, from the social viewpoint, the strategies of individuals can give rise to distinct outcomes. Namely, the rational behavior of individuals plays a ‘double-edged-sword’ role on the social effects.     

Spatial evolutionary game with bond dilution

In this paper, we study numerically the prisoner’s dilemma game (PDG) and snowdrift game (SG) on a two-dimensional square lattice with both quenched and annealed bond dilution. For quenched bond dilution, the system undergoes a dynamical transition at the critical occupation probability q^∗, which is higher than the bond percolation transition point for a square lattice. In the critical region, the defined order parameter has a scaling form as P_e∼(q−q^∗)^β for q<q^∗ with the critical exponents β=1.42 for PDG and β=1.52 for SG, which differ from those with quenched site dilution. For annealed bond dilution, the system exhibits a distinct cooperative behavior. We find that the cooperation is much enhanced in the range of small payoff parameters on a lattice with slightly annealed bond dilution.