Understanding the role of neutral species by means of high-order interaction in the rock-paper-scissors dynamics.

The existence of neutral species carries profound ecological implications that warrant further investigation. In this paper, we study the impact of neutral species on biodiversity in a spatial tritrophic system of cyclic competition, in which the neutral species are identified as the fourth species that may affect the competition process of the other three species under the rock-paper-scissors (RPS) rule. Extensive simulations showed that neutral species can promote coexistence in a high mobility regime within the system. When coexistence occurs, we found that the state can be maintained by two mechanisms: Species can either (i) adhere to traditional RPS rule or (ii) form patches to resist invasion. Our findings might aid in understanding the impact of neutral species on biodiversity in ecosystems.

Assessing the medical resources in COVID-19 based on evolutionary game.

COVID-19 has brought a great challenge to the medical system. A key scientific question is how to make a balance between home quarantine and staying in the hospital. To this end, we propose a game-based susceptible-exposed-asymptomatic -symptomatic- hospitalized-recovery-dead model to reveal such a situation. In this new framework, time-varying cure rate and mortality are employed and a parameter m is introduced to regulate the probability that individuals are willing to go to the hospital. Through extensive simulations, we find that (1) for low transmission rates (ß < 0.2), the high value of m (the willingness to stay in the hospital) indicates the full use of medical resources, and thus the pandemic can be easily contained; (2) for high transmission rates (ß > 0.2), large values of m lead to breakdown of the healthcare system, which will further increase the cumulative number of confirmed cases and death cases. Finally, we conduct the empirical analysis using the data from Japan and other typical countries to illustrate the proposed model and to test how our model explains reality.

The influence of heterogeneous learning ability on the evolution of cooperation.

In this paper, we design a simple coevolution model to investigate the role of heterogeneous learning ability on the evolution of cooperation. The model weakens the winner's learning ability in order to keep its current advantage. Conversely, it strengthens the loser's learning ability for increasing the chance to update its strategy. In particular, we consider this coevolutionary model separately applying to both cooperators and defectors (rule I), only cooperators (rule II), as well as only defectors (rule III) in spatial prisoner's dilemma game. Through numerical simulations, we find that cooperation can be promoted in rule II, whereas, cooperation is hampered in rule I and rule III. We reveal its potential reason from the viewpoint of enduring and expanding periods in game dynamics. Our results thus provide a deeper understanding regarding the heterogeneous learning ability on game theory.

Aspiration induced interdependence leads to optimal cooperation level.

How to couple different networks is a key issue in interdependent networks, where information sharing and payoff coupling are two frequently used methods. Unlike previous studies, in this paper, we propose a new coupling mode and test its performance in interdependent networks. Specifically, a player tends to seek additional support on another network only if his environment (defined as the proportion of holding different strategies in the neighborhood) is worse enough and exceeds an aspiration level. Conversely, it turns to the traditional version on single network if his environment is pleasing enough (the value of environment is small). Whether to establish additional support will directly influence the range of selecting fittest learning objects. As we can see from numerical results, moderate aspiration introduces diversity into the system and cooperation evolves with the support of network coupling. Besides, we also demonstrate that players with external links on the boundary of cooperative clusters protect internal cooperators and attract more players to cooperate under preferential selection rule.

The effect of asymmetric reproductive ability on the evolution of cooperation on interdependent networks.

In this paper, we consider an asymmetric reproductive ability on interdependent networks and investigate how this setting affects the evolution of cooperation. In detail, players decide to update their strategies at each step on main network (network B), while for sub network (network A), players update their strategies with a fixed probability p. Obviously, the system restores the traditional case when p = 1, where cooperation can survive by interdependent network reciprocity. And our asymmetric set-up comes into play when p < 1. Numerical simulation results show that our asymmetric coupling will hinder the overall cooperation level for small p. In detail, the introduction of asymmetric reproductive ability urges the formation of symmetry breaking and further weakens the positive impact by location synchronous effect. And the root cause is entirely distinct situation of utility differences on two networks. These observations further demonstrate a class of phenomena on interdependent networks that it would have catastrophic consequences on one network even if a unrelated change only occurs seemingly on another network.

Cooperation enhanced by the coevolution of teaching activity in evolutionary prisoner's dilemma games with voluntary participation.

Voluntary participation, as an additional strategy involved in repeated games, has been proved to be an efficient way to promote the evolution of cooperation theoretically and empirically. Besides, current studies show that the coevolution of teaching activity can promote cooperation. Thus, inspired by aforementioned above, we investigate the effect of coevolution of teaching activity on the evolution of cooperation for prisoner's dilemma game with voluntary participation: when the focal player successfully enforces its strategy on the opponent, his teaching ability will get an increase. Through numerical simulation, we have shown that voluntary participation could effectively promote the fraction of cooperation, which is also affected by the value of increment. Furthermore, we investigate the influence of the increment value on the density of different strategies and find that there exists an optimal increment value that plays an utmost role on the evolutionary dynamics. With regard to this observation, we unveil that an optimal value of increment can lead to strongest heterogeneity in agents' teaching ability, further promoting the evolution of cooperation.