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Why would natural selection favor the prevalence of cooperation within the groups of selfish individuals? A fruitful framework to address this question is evolutionary game theory, the essence of which is captured in the so-called social dilemmas. Voluntary participation is considered as an effective approach to promote the persistence of cooperative behavior. Because three strategic types of players lead to a rock–scissor–paper dynamic with cyclic dominance. There is no doubt that loner has played a very important role. Thus we introduce a parameter p represents loners’ participation willingness in order to explore the impact of its on cooperation in voluntary prisoner's dilemma. Large quantities of simulations demonstrate that for traditional case ( p = 1 ), three strategies will coexist. However, with p decreases, loners will greatly increase, and cooperation level declines, because defectors can be suppressed very fast. More interesting, when defectors completely vanish, cooperation becomes the best strategy, and holds the whole system. Thus our work present a viable method of understand the ubiquitous cooperative behaviors in nature and hope that it will inspire further studies to resolve social dilemmas. [ABSTRACT FROM AUTHOR]

Many literatures suggest that incorporating the environment of a focal player (denoted by the average payoff of its all immediate neighbors) into its fitness can promote cooperation in spatial evolutionary games. However, the immediate neighbors influence the focal one to varying degree. Inspired by these, we quantify the focal player's environment with a weighted average payoff of its all immediate neighbors via two interdependent parameters. Numerous simulations show that two moderate parameter pairs favor cooperation, in addition, when the contribution of all immediate neighbors’ payoffs to the environment is negative, the cooperation is promoted remarkably. The generality of this mechanism is verified on different networks and more games. Our work might shed light on the understanding of the evolution of cooperative behaviors in real life. [ABSTRACT FROM AUTHOR]

• We consider a population fragmented into cooperative and competitive units, i.e. we account explicitly for the two fundamental adaptation mechanisms at the basis of dynamical competition and cooperation (or interdependence) in networks. • Not only we reveal that the type of transition can in fact be controlled simply by adapting the balance between the two oscillator types. • We examine the role of different graph's mesoscales in the feedback leading to adaption, we show that the irreversibility associated to ES is actually enhanced when the adaptation mechanisms span larger scales. Synchronization is a subject of interdisciplinary relevance, interpolating between efficiency in transportation and digital data transfers to disease in cardiac and neural tissue. While continuous transitions to synchronization are gradual and easy to control, explosive transitions may occur suddenly and can have catastrophic effects. Here we report that in populations of cooperative and competitive oscillators the transition can be tuned between continuous and explosive simply by adjusting the balance between the two oscillator types. We show that this phenomenon is independent of the network topology, and can be described analytically already in the mean-field approximation. Moreover, we provide evidence that the difference between the two transitions is due to a merging process of clusters which is forbidden by adaptation, and that the hysteresis associated to the explosive transition is enhanced when the adaptive mechanisms span larger scales. [ABSTRACT FROM AUTHOR]