Metric clusters in evolutionary games on scale-free networks

The evolution of cooperation in social dilemmas in structured populations has been studied extensively in recent years. Whereas many theoretical studies have found that a heterogeneous network of contacts favors cooperation, the impact of spatial effects in scale-free networks is still not well understood. In addition to being heterogeneous, real contact networks exhibit a high mean local clustering coefficient, which implies the existence of an underlying metric space. Here, we show that evolutionary dynamics in scale-free networks self-organize into spatial patterns in the underlying metric space. The resulting metric clusters of cooperators are able to survive in social dilemmas as their spatial organization shields them from surrounding defectors, similar to spatial selection in Euclidean space. We show that under certain conditions these metric clusters are more efficient than the most connected nodes at sustaining cooperation and that heterogeneity does not always favor--but can even hinder--cooperation in social dilemmas. Our findings provide a new perspective to understand the emergence of cooperation in evolutionary games in realistic structured populations

Improving detection probabilities for pests in stored grain

BACKGROUND: The presence of insects in stored grains is a significant problem for grain farmers, bulk grain handlers and distributors worldwide. Inspections of bulk grain commodities is essential to detect pests and therefore to reduce the risk of their presence in exported goods. It has been well documented that insect pests cluster in response to factors such as microclimatic conditions within bulk grain. Statistical sampling methodologies for grains, however, have typically considered pests and pathogens to be homogeneously distributed throughout grain commodities. In this paper we demonstrate a sampling methodology that accounts for the heterogeneous distribution of insects in bulk grains. RESULTS: We show that failure to account for the heterogeneous distribution of pests may lead to overestimates of the capacity for a sampling program to detect insects in bulk grains. Our results indicate the importance of the proportion of grain that is infested in addition to the density of pests within the infested grain. We also demonstrate that the probability of detecting pests in bulk grains increases as the number of sub-samples increases, even when the total volume or mass of grain sampled remains constant. CONCLUSION: This study demonstrates the importance of considering an appropriate biological model when developing sampling methodologies for insect pests. Accounting for a heterogeneous distribution of pests leads to a considerable improvement in the detection of pests over traditional sampling models

Effect of Local Population Uncertainty on Cooperation in Bacteria

Bacteria populations rely on mechanisms such as quorum sensing to coordinate complex tasks that cannot be achieved by a single bacterium. Quorum sensing is used to measure the local bacteria population density, and it controls cooperation by ensuring that a bacterium only commits the resources for cooperation when it expects its neighbors to reciprocate. This paper proposes a simple model for sharing a resource in a bacterial environment, where knowledge of the population influences each bacterium's behavior. Game theory is used to model the behavioral dynamics, where the net payoff (i.e., utility) for each bacterium is a function of its current behavior and that of the other bacteria. The game is first evaluated with perfect knowledge of the population. Then, the unreliability of diffusion introduces uncertainty in the local population estimate and changes the perceived payoffs. The results demonstrate the sensitivity to the system parameters and how population uncertainty can overcome a lack of explicit coordination.Comment: 5 pages, 6 figures. Will be presented as an invited paper at the 2017 IEEE Information Theory Workshop in November 2017 in Kaohsiung, Taiwa

De-commoditizing Ethiopian coffees after the establishment of the Ethiopian Commodity Exchange : an empirical investigation of smallholder coffee producers in Ethiopia

The repercussions of reforming an agricultural market are mainly observed at the most vulnerable segment of the value chain, namely, the producers. In the current commodity market created with trade through the Ethiopian Commodity Exchange (ECX), coffee is less traceable to its producers. Only cooperatives that sell certified coffee through the unions they belong to, are allowed to bypass the more commodified ECX market. This study aims to investigate if small-scale coffee producers in southwestern Ethiopia that sell coffee through the certified cooperative are better off. It is assumed that the coffee sales through, and membership of, a cooperative, allows farmers to improve their coffee production as well as to improve other aspects of their livelihood. A sustainable livelihood approach was used as the inspiration for the welfare indicators that needed to be considered, data collected amongst members and non-members of certified cooperatives, and a propensity score model to investigate the impact of cooperative membership on the livelihood indicators. Results suggest that members of certified cooperatives indeed receive, on average, better prices. Yet, no evidence was found that indicates that the higher price is translated into better household income. Furthermore, coffee plantation productivity of those members who were interviewed was lower than that of the non-members. This finding could explain the failure to find an overall effect. Since the majority of the producers' income emanate from coffee, a sustainable way of enhancing the productivity of the coffee could revitalize the welfare of the coffee producers

A Game-Theoretic Study on Non-Monetary Incentives in Data Analytics Projects with Privacy Implications

The amount of personal information contributed by individuals to digital repositories such as social network sites has grown substantially. The existence of this data offers unprecedented opportunities for data analytics research in various domains of societal importance including medicine and public policy. The results of these analyses can be considered a public good which benefits data contributors as well as individuals who are not making their data available. At the same time, the release of personal information carries perceived and actual privacy risks to the contributors. Our research addresses this problem area. In our work, we study a game-theoretic model in which individuals take control over participation in data analytics projects in two ways: 1) individuals can contribute data at a self-chosen level of precision, and 2) individuals can decide whether they want to contribute at all (or not). From the analyst's perspective, we investigate to which degree the research analyst has flexibility to set requirements for data precision, so that individuals are still willing to contribute to the project, and the quality of the estimation improves. We study this tradeoff scenario for populations of homogeneous and heterogeneous individuals, and determine Nash equilibria that reflect the optimal level of participation and precision of contributions. We further prove that the analyst can substantially increase the accuracy of the analysis by imposing a lower bound on the precision of the data that users can reveal

WHO DO YOU TRUST? ETHNICITY AND TRUST IN BOSNIA AND HERZEGOVINA

Bosnia and Herzegovina has experienced a turbulent post-independence transition. It can be argued that the level of trust is likely to have been negatively affected by this turbulence and that it is important to restore trust to achieve sustainable political and economic development. This paper looks at trust in Bosnia and Herzegovina and puts a special focus on the role of ethnicity. We find generalized trust to be low in Bosnia and Herzegovina and it seems to have declined in recent years. Moreover, generalized trust is negatively affected by the degree of ethnic heterogeneity in the region. However, a further and more detailed examination of trust reveals a more complex relationship between ethnicity and trust: people tend to show low levels of trust in all other people irrespective of their ethnic belongings. We argue that ethnic distribution might capture some other regional specific characteristics that also affect the level of trust. One possibility is that ethnically heterogeneous regions tended to be severely affected by the war and that this has negatively affected the level of trust towards all people outside of a person’s family.Trust; Social Capital; Ethnicity; Southeast Europe; Bosnia and Herzegovina

Parallel memetic algorithms for independent job scheduling in computational grids

In this chapter we present parallel implementations of Memetic Algorithms (MAs) for the problem of scheduling independent jobs in computational grids. The problem of scheduling in computational grids is known for its high demanding computational time. In this work we exploit the intrinsic parallel nature of MAs as well as the fact that computational grids offer large amount of resources, a part of which could be used to compute the efficient allocation of jobs to grid resources. The parallel models exploited in this work for MAs include both fine-grained and coarse-grained parallelization and their hybridization. The resulting schedulers have been tested through different grid scenarios generated by a grid simulator to match different possible configurations of computational grids in terms of size (number of jobs and resources) and computational characteristics of resources. All in all, the result of this work showed that Parallel MAs are very good alternatives in order to match different performance requirement on fast scheduling of jobs to grid resources.Peer ReviewedPostprint (author's final draft