Optimal interdependence between networks for the evolution of cooperation

Recent research has identified interactions between networks as crucial for the outcome of evolutionary games taking place on them. While the consensus is that interdependence does promote cooperation by means of organizational complexity and enhanced reciprocity that is out of reach on isolated networks, we here address the question just how much interdependence there should be. Intuitively, one might assume the more the better. However, we show that in fact only an intermediate density of sufficiently strong interactions between networks warrants an optimal resolution of social dilemmas. This is due to an intricate interplay between the heterogeneity that causes an asymmetric strategy flow because of the additional links between the networks, and the independent formation of cooperative patterns on each individual network. Presented results are robust to variations of the strategy updating rule, the topology of interdependent networks, and the governing social dilemma, thus suggesting a high degree of universality

Cooperation, Norms, and Revolutions: A Unified Game-Theoretical Approach

Cooperation is of utmost importance to society as a whole, but is often challenged by individual self-interests. While game theory has studied this problem extensively, there is little work on interactions within and across groups with different preferences or beliefs. Yet, people from different social or cultural backgrounds often meet and interact. This can yield conflict, since behavior that is considered cooperative by one population might be perceived as non-cooperative from the viewpoint of another. To understand the dynamics and outcome of the competitive interactions within and between groups, we study game-dynamical replicator equations for multiple populations with incompatible interests and different power (be this due to different population sizes, material resources, social capital, or other factors). These equations allow us to address various important questions: For example, can cooperation in the prisoner's dilemma be promoted, when two interacting groups have different preferences? Under what conditions can costly punishment, or other mechanisms, foster the evolution of norms? When does cooperation fail, leading to antagonistic behavior, conflict, or even revolutions? And what incentives are needed to reach peaceful agreements between groups with conflicting interests? Our detailed quantitative analysis reveals a large variety of interesting results, which are relevant for society, law and economics, and have implications for the evolution of language and culture as well

Overconfidence in Labor Markets

This chapter reviews how worker overconfidence affects labor markets. Evidence from psychology and economics shows that in many situations, most people tend to overestimate their absolute skills, overplace themselves relative to others, and overestimate the precision of their knowledge. The chapter starts by reviewing evidence for overconfidence and for how overconfidence affects economic choices. Next, it reviews economic explanations for overconfidence. After that, it discusses research on the impact of worker overconfidence on labor markets where wages are determined by bargaining between workers and firms. Here, three key questions are addressed. First, how does worker overconfidence affect effort provision for a fixed compensation scheme? Second, how should firms design compensation schemes when workers are overconfident? In particular, will a compensation scheme offered to an overconfident worker have higher-or lower-powered incentives than that offered to a worker with accurate self-perception? Third, can worker overconfidence lead to a Pareto improvement? The chapter continues by reviewing research on the impact of worker overconfidence on labor markets where workers can move between firms and where neither firms nor workers have discretion over wage setting. The chapter concludes with a summary of its main findings and a discussion of avenues for future research

Influence of opinion dynamics on the evolution of games

Under certain circumstances such as lack of information or bounded rationality, human players can take decisions on which strategy to choose in a game on the basis of simple opinions. These opinions can be modified after each round by observing own or others payoff results but can be also modified after interchanging impressions with other players. In this way, the update of the strategies can become a question that goes beyond simple evolutionary rules based on fitness and become a social issue. In this work, we explore this scenario by coupling a game with an opinion dynamics model. The opinion is represented by a continuous variable that corresponds to the certainty of the agents respect to which strategy is best. The opinions transform into actions by making the selection of an strategy a stochastic event with a probability regulated by the opinion. A certain regard for the previous round payoff is included but the main update rules of the opinion are given by a model inspired in social interchanges. We find that the dynamics fixed points of the coupled model is different from those of the evolutionary game or the opinion models alone. Furthermore, new features emerge such as the resilience of the fraction of cooperators to the topology of the social interaction network or to the presence of a small fraction of extremist players.Comment: 7 pages, 5 figure

Heterogeneous Aspirations Promote Cooperation in the Prisoner's Dilemma Game

To be the fittest is central to proliferation in evolutionary games. Individuals thus adopt the strategies of better performing players in the hope of successful reproduction. In structured populations the array of those that are eligible to act as strategy sources is bounded to the immediate neighbors of each individual. But which one of these strategy sources should potentially be copied? Previous research dealt with this question either by selecting the fittest or by selecting one player uniformly at random. Here we introduce a parameter that interpolates between these two extreme options. Setting equal to zero returns the random selection of the opponent, while positive favor the fitter players. In addition, we divide the population into two groups. Players from group select their opponents as dictated by the parameter , while players from group do so randomly irrespective of . We denote the fraction of players contained in groups and by and , respectively. The two parameters and allow us to analyze in detail how aspirations in the context of the prisoner's dilemma game influence the evolution of cooperation. We find that for sufficiently positive values of there exist a robust intermediate for which cooperation thrives best. The robustness of this observation is tested against different levels of uncertainty in the strategy adoption process and for different interaction networks. We also provide complete phase diagrams depicting the dependence of the impact of and for different values of , and contrast the validity of our conclusions by means of an alternative model where individual aspiration levels are subject to evolution as well. Our study indicates that heterogeneity in aspirations may be key for the sustainability of cooperation in structured populations

Response of Methicillin-Resistant Staphylococcus aureus to Amicoumacin A

Amicoumacin A exhibits strong antimicrobial activity against methicillin-resistant Staphylococcus aureus (MRSA), hence we sought to uncover its mechanism of action. Genome-wide transcriptome analysis of S. aureus COL in response to amicoumacin A showed alteration in transcription of genes specifying several cellular processes including cell envelope turnover, cross-membrane transport, virulence, metabolism, and general stress response. The most highly induced gene was lrgA, encoding an antiholin-like product, which is induced in cells undergoing a collapse of Δψ. Consistent with the notion that LrgA modulates murein hydrolase activity, COL grown in the presence of amicoumacin A showed reduced autolysis, which was primarily caused by lower hydrolase activity. To gain further insight into the mechanism of action of amicoumacin A, a whole genome comparison of wild-type COL and amicoumacin A-resistant mutants isolated by a serial passage method was carried out. Single point mutations generating codon substitutions were uncovered in ksgA (encoding RNA dimethyltransferase), fusA (elongation factor G), dnaG (primase), lacD (tagatose 1,6-bisphosphate aldolase), and SACOL0611 (a putative glycosyl transferase). The codon substitutions in EF-G that cause amicoumacin A resistance and fusidic acid resistance reside in separate domains and do not bring about cross resistance. Taken together, these results suggest that amicoumacin A might cause perturbation of the cell membrane and lead to energy dissipation. Decreased rates of cellular metabolism including protein synthesis and DNA replication in resistant strains might allow cells to compensate for membrane dysfunction and thus increase cell survivability

Pay-off scarcity causes evolution of risk-aversion and extreme altruism

All organisms descend from populations with limited resources, so it is clear why evolution should select strategies that win resources at the expense of competitors. Less obvious is how altruistic behaviours evolve, whereby an individual helps others despite expense to itself. Modelling simple agents using evolutionary game theory, it is shown that steady states of extreme altruism can evolve when pay-offs are very rare compared with death. In these states, agents give away most of their wealth. A new theorem for general evolutionary models shows that, when pay-offs are rare, evolution no longer selects strategies to maximize income (average pay-off), but to minimize the risk of missing-out entirely on a rare resource. Principles revealed by the model are widely applicable, where the game represents rare life-changing events: disasters or gluts

Giving in the Face of Risk

The decision how to share resources with others often needs to be taken under uncertainty on its allocational consequences. Although risk preferences are likely important, existing research is silent about how social and risk preferences interact in such situations. In this paper we provide experimental evidence on this question. In a first experiment givers are not exposed to risk while beneficiaries’ final earnings may be larger or smaller than the allocation itself, depending on the realized state of the world. In a second experiment, risk affects the earnings of givers but not of beneficiaries. We find that individuals’ risk preferences are predictive for giving in both experiments. Increased risk exposure of beneficiaries tends to decrease giving whereas increased risk exposure of givers has no effect. Giving under risk is strongly correlated with giving in the absence of risk. We find limited support for existing models of ex-post and ex-ante fairness. Our results point to the importance of incorporating risk preferences in models of social preferences

Mitochondrial dysfunction and biogenesis: do ICU patients die from mitochondrial failure?

Mitochondrial functions include production of energy, activation of programmed cell death, and a number of cell specific tasks, e.g., cell signaling, control of Ca2+ metabolism, and synthesis of a number of important biomolecules. As proper mitochondrial function is critical for normal performance and survival of cells, mitochondrial dysfunction often leads to pathological conditions resulting in various human diseases. Recently mitochondrial dysfunction has been linked to multiple organ failure (MOF) often leading to the death of critical care patients. However, there are two main reasons why this insight did not generate an adequate resonance in clinical settings. First, most data regarding mitochondrial dysfunction in organs susceptible to failure in critical care diseases (liver, kidney, heart, lung, intestine, brain) were collected using animal models. Second, there is no clear therapeutic strategy how acquired mitochondrial dysfunction can be improved. Only the benefit of such therapies will confirm the critical role of mitochondrial dysfunction in clinical settings. Here we summarized data on mitochondrial dysfunction obtained in diverse experimental systems, which are related to conditions seen in intensive care unit (ICU) patients. Particular attention is given to mechanisms that cause cell death and organ dysfunction and to prospective therapeutic strategies, directed to recover mitochondrial function. Collectively the data discussed in this review suggest that appropriate diagnosis and specific treatment of mitochondrial dysfunction in ICU patients may significantly improve the clinical outcome

Measurement of the tt¯tt¯ production cross section in pp collisions at √s=13 TeV with the ATLAS detector

A measurement of four-top-quark production using proton-proton collision data at a centre-of-mass energy of 13 TeV collected by the ATLAS detector at the Large Hadron Collider corresponding to an integrated luminosity of 139 fb−1 is presented. Events are selected if they contain a single lepton (electron or muon) or an opposite-sign lepton pair, in association with multiple jets. The events are categorised according to the number of jets and how likely these are to contain b-hadrons. A multivariate technique is then used to discriminate between signal and background events. The measured four-top-quark production cross section is found to be 26+17−15 fb, with a corresponding observed (expected) significance of 1.9 (1.0) standard deviations over the background-only hypothesis. The result is combined with the previous measurement performed by the ATLAS Collaboration in the multilepton final state. The combined four-top-quark production cross section is measured to be 24+7−6 fb, with a corresponding observed (expected) signal significance of 4.7 (2.6) standard deviations over the background-only predictions. It is consistent within 2.0 standard deviations with the Standard Model expectation of 12.0 ± 2.4 fb