Heinrich H. Nax

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We study evolutionary dynamics in assignment games where many agents interact anonymously at virtually no cost. The process is decentralized, very little information is available and trade takes place at many different prices simultaneously. We propose a completely uncoupled learning process that selects a subset of the core of the game with a natural(More)
BACKGROUND Since late 2015, an epidemic of yellow fever has caused more than 7334 suspected cases in Angola and the Democratic Republic of the Congo, including 393 deaths. We sought to understand the spatial spread of this outbreak to optimise the use of the limited available vaccine stock. METHODS We jointly analysed datasets describing the epidemic of(More)
Image scoring sustains cooperation in the repeated two-player prisoner's dilemma through indirect reciprocity, even though defection is the uniquely dominant selfish behaviour in the one-shot game. Many real-world dilemma situations, however, firstly, take place in groups and, secondly, lack the necessary transparency to inform subjects reliably of others'(More)
Payoff-driven adjustment dynamics lead to stable and optimal outcomes in decentralized two-sided assignment markets. Pairs of agents from both sides of the market randomly encounter each other and match if `profitable'. Very little information is available, in particular agents have no knowledge of others' preferences, their past actions and payoffs or the(More)
Economic games such as the public goods game are increasingly being used to measure social behaviours in humans and non-human primates. The results of such games have been used to argue that people are pro-social, and that humans are uniquely altruistic, willingly sacrificing their own welfare in order to benefit others. However, an alternative explanation(More)
Many interactive environments can be represented as games, but they are so large and complex that individual players are in the dark about others’ actions and the payoff structure. This paper analyzes learning behavior in such ‘black box’ environments, where players’ only source of information is their own history of actions taken and payoffs received.(More)
We consider an environment where players are involved in a public goods game and must decide repeatedly whether to make an individual contribution or not. However, players lack strategically relevant information about the game and about the other players in the population. The resulting behavior of players is completely uncoupled from such information, and(More)
‘Noise’ in this study, in the sense of evolutionary game theory, refers to deviations from prevailing behavioral rules. Analyzing data from a laboratory experiment on coordination in networks, we tested ‘what kind of noise’ is supported by behavioral evidence. This empirical analysis complements a growing theoretical literature on ‘how noise matters’ for(More)
Assortative mechanisms can overcome tragedies of the commons that otherwise result in dilemma situations. Assortativity criteria include various forms of kin selection, greenbeard genes, and reciprocal behaviors, usually presuming an exogenously fixed matching mechanism. Here, we endogenize the matching process with the aim of investigating how(More)
Decentralized matching platforms on the internet allow large numbers of agents to interact anonymously at virtually no cost. Very little information is available to market participants and trade takes place at many different prices simultaneously. We propose a decentralized, completely uncoupled learning process in such environments that leads to stable and(More)