48,901 research outputs found
Coveting thy neighbors fitness as a means to resolve social dilemmas
In spatial evolutionary games the fitness of each individual is traditionally
determined by the payoffs it obtains upon playing the game with its neighbors.
Since defection yields the highest individual benefits, the outlook for
cooperators is gloomy. While network reciprocity promotes collaborative
efforts, chances of averting the impending social decline are slim if the
temptation to defect is strong. It is therefore of interest to identify viable
mechanisms that provide additional support for the evolution of cooperation.
Inspired by the fact that the environment may be just as important as
inheritance for individual development, we introduce a simple switch that
allows a player to either keep its original payoff or use the average payoff of
all its neighbors. Depending on which payoff is higher, the influence of either
option can be tuned by means of a single parameter. We show that, in general,
taking into account the environment promotes cooperation. Yet coveting the
fitness of one's neighbors too strongly is not optimal. In fact, cooperation
thrives best only if the influence of payoffs obtained in the traditional way
is equal to that of the average payoff of the neighborhood. We present results
for the prisoner's dilemma and the snowdrift game, for different levels of
uncertainty governing the strategy adoption process, and for different
neighborhood sizes. Our approach outlines a viable route to increased levels of
cooperative behavior in structured populations, but one that requires a
thoughtful implementation.Comment: 10 two-column pages, 5 figures; accepted for publication in Journal
of Theoretical Biolog
Leaders should not be conformists in evolutionary social dilemmas
The most common assumption in evolutionary game theory is that players should
adopt a strategy that warrants the highest payoff. However, recent studies
indicate that the spatial selection for cooperation is enhanced if an
appropriate fraction of the population chooses the most common rather than the
most profitable strategy within the interaction range. Such conformity might be
due to herding instincts or crowd behavior in humans and social animals. In a
heterogeneous population where individuals differ in their degree, collective
influence, or other traits, an unanswered question remains who should conform.
Selecting conformists randomly is the simplest choice, but it is neither a
realistic nor the optimal one. We show that, regardless of the source of
heterogeneity and game parametrization, socially the most favorable outcomes
emerge if the masses conform. On the other hand, forcing leaders to conform
significantly hinders the constructive interplay between heterogeneity and
coordination, leading to evolutionary outcomes that are worse still than if
conformists were chosen randomly. We conclude that leaders must be able to
create a following for network reciprocity to be optimally augmented by
conformity. In the opposite case, when leaders are castrated and made to
follow, the failure of coordination impairs the evolution of cooperation.Comment: 7 two-column pages, 4 figures; accepted for publication in Scientific
Reports [related work available at arXiv:1412.4113
The Advantage of Evidential Attributes in Social Networks
Nowadays, there are many approaches designed for the task of detecting
communities in social networks. Among them, some methods only consider the
topological graph structure, while others take use of both the graph structure
and the node attributes. In real-world networks, there are many uncertain and
noisy attributes in the graph. In this paper, we will present how we detect
communities in graphs with uncertain attributes in the first step. The
numerical, probabilistic as well as evidential attributes are generated
according to the graph structure. In the second step, some noise will be added
to the attributes. We perform experiments on graphs with different types of
attributes and compare the detection results in terms of the Normalized Mutual
Information (NMI) values. The experimental results show that the clustering
with evidential attributes gives better results comparing to those with
probabilistic and numerical attributes. This illustrates the advantages of
evidential attributes.Comment: 20th International Conference on Information Fusion, Jul 2017, Xi'an,
Chin
Some Job Contacts are More Equal Than Others: Earnings and Job Information Networks
There is considerable disagreement about the effects of informal contacts on earnings. Some researchers report higher earnings for those who found their jobs through such contacts, some report lower earnings, and some report no effects. This paper uses data from the National Longitudinal Survey of Youth to address this issue. When contact effects for young male and female workers were measured in the aggregate, those who found their jobs through informal contacts fared no better than those using formal methods. However, if subgroup contact effects were measured, those who found their jobs through prior-generation male relatives most likely to convey high quality information to employers and workers earned at least 13 percent more than those using formal and other informal methods. This means that job network analyses should not focus exclusively on the use of informal contacts but should distinguish between contacts based on what they can potentially provide for jobseekers.
Low-Cost Air Quality Monitoring Tools: From Research to Practice (A Workshop Summary).
In May 2017, a two-day workshop was held in Los Angeles (California, U.S.A.) to gather practitioners who work with low-cost sensors used to make air quality measurements. The community of practice included individuals from academia, industry, non-profit groups, community-based organizations, and regulatory agencies. The group gathered to share knowledge developed from a variety of pilot projects in hopes of advancing the collective knowledge about how best to use low-cost air quality sensors. Panel discussion topics included: (1) best practices for deployment and calibration of low-cost sensor systems, (2) data standardization efforts and database design, (3) advances in sensor calibration, data management, and data analysis and visualization, and (4) lessons learned from research/community partnerships to encourage purposeful use of sensors and create change/action. Panel discussions summarized knowledge advances and project successes while also highlighting the questions, unresolved issues, and technological limitations that still remain within the low-cost air quality sensor arena
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