34,616 research outputs found
Evolution of Coordination in Social Networks: A Numerical Study
Coordination games are important to explain efficient and desirable social
behavior. Here we study these games by extensive numerical simulation on
networked social structures using an evolutionary approach. We show that local
network effects may promote selection of efficient equilibria in both pure and
general coordination games and may explain social polarization. These results
are put into perspective with respect to known theoretical results. The main
insight we obtain is that clustering, and especially community structure in
social networks has a positive role in promoting socially efficient outcomes.Comment: preprint submitted to IJMP
Evolutionary Dilemmas in a Social Network
We simulate the prisoner's dilemma and hawk-dove games on a real social
acquaintance network. Using a discrete analogue of replicator dynamics, we show
that surprisingly high levels of cooperation can be achieved, contrary to what
happens in unstructured mixing populations. Moreover, we empirically show that
cooperation in this network is stable with respect to invasion by defectors.Comment: 13 pages, 9 figures; to be published in Lecture Notes in Computer
Science 200
Collaboration in sensor network research: an in-depth longitudinal analysis of assortative mixing patterns
Many investigations of scientific collaboration are based on statistical
analyses of large networks constructed from bibliographic repositories. These
investigations often rely on a wealth of bibliographic data, but very little or
no other information about the individuals in the network, and thus, fail to
illustrate the broader social and academic landscape in which collaboration
takes place. In this article, we perform an in-depth longitudinal analysis of a
relatively small network of scientific collaboration (N = 291) constructed from
the bibliographic record of a research center involved in the development and
application of sensor network and wireless technologies. We perform a
preliminary analysis of selected structural properties of the network,
computing its range, configuration and topology. We then support our
preliminary statistical analysis with an in-depth temporal investigation of the
assortative mixing of selected node characteristics, unveiling the researchers'
propensity to collaborate preferentially with others with a similar academic
profile. Our qualitative analysis of mixing patterns offers clues as to the
nature of the scientific community being modeled in relation to its
organizational, disciplinary, institutional, and international arrangements of
collaboration.Comment: Scientometrics (In press
Ghent University Technology Park : from a local initiative towards an essential component of the Ghent knowledge innovation ecosystem
Using the case of the Ghent University and its Technology Park, we will illustrate how changing policies and practices at the level of the university concerning research valorization have an impact on our science park. We will also demonstrate how the evolving nature of our science park has a clear impact on the university, as the science park becomes more and more an integral part of the university knowledge eco-system. We will also highlight the involvement of Ghent University in the Korea Songdo Global University Campus Project
The Complex Network of Evolutionary Computation Authors: an Initial Study
EC paper authors form a complex network of co-authorship which is, by itself,
a example of an evolving system with its own rules, concept of fitness, and
patterns of attachment. In this paper we explore the network of authors of
evolutionary computation papers found in a major bibliographic database. We
examine its macroscopic properties, and compare it with other co-authorship
networks; the EC co-authorship network yields results in the same ballpark as
other networks, but exhibits some distinctive patterns in terms of internal
cohesion. We also try to find some hints on what makes an author a sociometric
star. Finally, the role of proceeding editorship as the origin of long-range
links in the co-authorship network is studied as well.Comment: Sociometric study of the Evolutionary Computation community.
Submitted to Evolutionary Computation lette
An Order-based Algorithm for Minimum Dominating Set with Application in Graph Mining
Dominating set is a set of vertices of a graph such that all other vertices
have a neighbour in the dominating set. We propose a new order-based randomised
local search (RLS) algorithm to solve minimum dominating set problem in
large graphs. Experimental evaluation is presented for multiple types of
problem instances. These instances include unit disk graphs, which represent a
model of wireless networks, random scale-free networks, as well as samples from
two social networks and real-world graphs studied in network science. Our
experiments indicate that RLS performs better than both a classical greedy
approximation algorithm and two metaheuristic algorithms based on ant colony
optimisation and local search. The order-based algorithm is able to find small
dominating sets for graphs with tens of thousands of vertices. In addition, we
propose a multi-start variant of RLS that is suitable for solving the
minimum weight dominating set problem. The application of RLS in graph
mining is also briefly demonstrated
Agents in Bioinformatics
The scope of the Technical Forum Group (TFG) on Agents in Bioinformatics (BIOAGENTS) was to inspire collaboration between the agent and bioinformatics communities with the aim of creating an opportunity to propose a different (agent-based) approach to the development of computational frameworks both for data analysis in bioinformatics and for system modelling in computational biology. During the day, the participants examined the future of research on agents in bioinformatics primarily through 12 invited talks selected to cover the most relevant topics. From the discussions, it became clear that there are many perspectives to the field, ranging from bio-conceptual languages for agent-based simulation, to the definition of bio-ontology-based declarative languages for use by information agents, and to the use of Grid agents, each of which requires further exploration. The interactions between participants encouraged the development of applications that describe a way of creating agent-based simulation models of biological systems, starting from an hypothesis and inferring new knowledge (or relations) by mining and analysing the huge amount of public biological data. In this report we summarise and reflect on the presentations and discussions
The SmartAG partner: CCAFS East Africa Bi-Annual Newsletter, July - December 2019
We are pleased to share with you our SmartAg Partner bi-annual newsletter, highlighting policy engagement, ongoing research, field updates and activities with partners from the second half of 2019
- …