Evolution of cooperation under social pressure in multiplex networks

In this work, we aim to contribute to the understanding of human prosocial behavior by studying the influence that a particular form of social pressure, "being watched," has on the evolution of cooperative behavior. We study how cooperation emerges in multiplex complex topologies by analyzing a particular bidirectionally coupled dynamics on top of a two-layer multiplex network (duplex). The coupled dynamics appears between the prisoner's dilemma game in a network and a threshold cascade model in the other. The threshold model is intended to abstract the behavior of a network of vigilant nodes that impose the pressure of being observed altering hence the temptation to defect of the dilemma. Cooperation or defection in the game also affects the state of a node of being vigilant. We analyze these processes on different duplex networks structures and assess the influence of the topology, average degree and correlated multiplexity, on the outcome of cooperation. Interestingly, we find that the social pressure of vigilance may impact cooperation positively or negatively, depending on the duplex structure, specifically the degree correlations between layers is determinant. Our results give further quantitative insights in the promotion of cooperation under social pressure.The author acknowledge support from the project H2020 FET OPEN RIA IBSEN/662725 and from Institute of Physics of Cantabria (IFCA-CSIC) for providing access to the Altamira supercomputer

Creating and Managing EU Funded Research Networks: An Exploratory Case

The collaborative European funded research and development landscape drives competitiveness among innovative organisations. Recently it has seen the rise of public private partnerships significantly impacting the dynamics of these networks. Thus, the complexity of managing research networks has intensified with the increased diversity of research network members. Additionally, the emergence of the academic entrepreneur has augmented the focus of educational institutions to include innovation and building start-up organisations. The impact of research is scalable if an optimum research network is created and managed effectively. This paper investigates network embeddedness; the nature of relationships, links and nodes within a research network, specifically their structure, configuration and quality. The contribution of this paper extends our understanding for establishing and maintaining effective collaborative research networks. The effects of network embeddedness are recognized in the literature as pertinent to innovation and the economy. Network theory literature claims that networks are essential to innovative clusters such as Silicon valley and innovation in high tech industries. The concept of embeddedness is what differentiates network theory from economic theory. This study adopts a qualitative approach and uncovers some of the challenges of multi-disciplinary research through case study insights. One challenge is competition between network members over ownership and sharing of data. The contribution of this paper recommends the establishment of scaffolding to accommodate cooperation in research networks, role appointment, and addressing contextual complexities early to avoid problem cultivation. Furthermore, it suggests recommendations in relation to network formation, incubation and operations. The network capability is enhanced by the recognition of network theory, open innovation and social exchange with the understanding that the network structure has an impact on innovation and social exchange in research networks and subsequently on research output. The research concludes that the success of collaborative research is reliant upon establishing a common language and understanding between network members to realise their research objectives

Coalitional Games for Distributed Collaborative Spectrum Sensing in Cognitive Radio Networks

Collaborative spectrum sensing among secondary users (SUs) in cognitive networks is shown to yield a significant performance improvement. However, there exists an inherent trade off between the gains in terms of probability of detection of the primary user (PU) and the costs in terms of false alarm probability. In this paper, we study the impact of this trade off on the topology and the dynamics of a network of SUs seeking to reduce the interference on the PU through collaborative sensing. Moreover, while existing literature mainly focused on centralized solutions for collaborative sensing, we propose distributed collaboration strategies through game theory. We model the problem as a non-transferable coalitional game, and propose a distributed algorithm for coalition formation through simple merge and split rules. Through the proposed algorithm, SUs can autonomously collaborate and self-organize into disjoint independent coalitions, while maximizing their detection probability taking into account the cooperation costs (in terms of false alarm). We study the stability of the resulting network structure, and show that a maximum number of SUs per formed coalition exists for the proposed utility model. Simulation results show that the proposed algorithm allows a reduction of up to 86.6% of the average missing probability per SU (probability of missing the detection of the PU) relative to the non-cooperative case, while maintaining a certain false alarm level. In addition, through simulations, we compare the performance of the proposed distributed solution with respect to an optimal centralized solution that minimizes the average missing probability per SU. Finally, the results also show how the proposed algorithm autonomously adapts the network topology to environmental changes such as mobility.Comment: in proceedings of IEEE INFOCOM 200

Social Networks in Wild Asses: Comparing Patterns and Processes among Populations

Asiatic wild asses inhabit some of the most arid environments in the world. All live in fissionfusion societies, but demography varies and the deserts in which they live often differ in subtle ways. Characterizing details of social structure of wild ass populations has been a challenge and has made it difficult to determine causes and consequences of any differences that might exist. We use network theory to compare the social structures of two populations of Asiatic asses/ onagers inhabiting the Negev desert, Israel and khur of the Little Rann of Kuch, India and show that populations differ in important structural ways that represent adaptive responses to variations in ecological demographic and phenotypic circumstances. Our analyses show that onagers inhabiting more variable environments then khur also live in larger, more cohesive groups than khur. Presumably networks with this structure facilitate the spread of information and foster cooperation. We also show that demography matters since social fragmentation increases as populations grow. Increases in the number of components in populations, reductions in the number of associates and diminished cliquishness within components, appear to be adaptive responses to integrating increasing numbers of individuals into social networks. We also find some support for the idea that social connectedness varies with phenotype. In our larger populations, non-lactating females who are most challenged in finding sparse feeding sites, are more selective than lactating females in their choice of strong associates. Presumably networks with this structure enhance foraging success by increasing information flow among like-minded individuals. As our study demonstrates, network analysis facilitates testing predictions about the cause of social structure and its impact on transmission processes

Incomplete Punishment Networks in Public Goods Games: Experimental Evidence

Abundant evidence suggests that high levels of contributions to public goods can be sustained through self-governed monitoring and sanctioning. This experimental study investigates the effectiveness of decentralized sanctioning institutions in alternative punishment networks. Our results show that the structure of punishment network significantly affects allocations to the public good. In addition, we observe that network configurations are more important than punishment capacities for the levels of public good provision, imposed sanctions and economic efficiency. Lastly, we show that targeted revenge is a major driver of anti-social punishment

Coevolutionary games - a mini review

Prevalence of cooperation within groups of selfish individuals is puzzling in that it contradicts with the basic premise of natural selection. Favoring players with higher fitness, the latter is key for understanding the challenges faced by cooperators when competing with defectors. Evolutionary game theory provides a competent theoretical framework for addressing the subtleties of cooperation in such situations, which are known as social dilemmas. Recent advances point towards the fact that the evolution of strategies alone may be insufficient to fully exploit the benefits offered by cooperative behavior. Indeed, while spatial structure and heterogeneity, for example, have been recognized as potent promoters of cooperation, coevolutionary rules can extend the potentials of such entities further, and even more importantly, lead to the understanding of their emergence. The introduction of coevolutionary rules to evolutionary games implies, that besides the evolution of strategies, another property may simultaneously be subject to evolution as well. Coevolutionary rules may affect the interaction network, the reproduction capability of players, their reputation, mobility or age. Here we review recent works on evolutionary games incorporating coevolutionary rules, as well as give a didactic description of potential pitfalls and misconceptions associated with the subject. In addition, we briefly outline directions for future research that we feel are promising, thereby particularly focusing on dynamical effects of coevolutionary rules on the evolution of cooperation, which are still widely open to research and thus hold promise of exciting new discoveries.Comment: 24 two-column pages, 10 figures; accepted for publication in BioSystem