109,664 research outputs found
Binding Social and Cultural Networks: A Model
Until now, most studies carried onto social or semantic networks have
considered each of these networks independently. Our goal here is to bring a
formal frame for studying both networks empirically as well as to point out
stylized facts that would explain their reciprocal influence and the emergence
of clusters of agents, which may also be regarded as ''cultural cliques''. We
show how to apply the Galois lattice theory to the modeling of the coevolution
of social and conceptual networks, and the characterization of cultural
communities. Basing our approach on Barabasi-Albert's models, we however extend
the usual preferential attachment probability in order to take into account the
reciprocal influence of both networks, therefore introducing the notion of dual
distance. In addition to providing a theoretic frame we draw here a program of
empirical tests which should give root to a more analytical model and the
consequent simulation and validation. In a broader view, adopting and actually
implementing the paradigm of cultural epidemiology, we could proceed further
with the study of knowledge diffusion and explain how the social network
structure affects concept propagation and in return how concept propagation
affects the social network.Comment: 8 pages, 3 figures (v2: typos, minor corrections in section 3.2) (v3:
examples, figures added
Information Modeling for a Dynamic Representation of an Emergency Situation
In this paper we propose an approach to build a decision support system that
can help emergency planners and responders to detect and manage emergency
situations. The internal mechanism of the system is independent from the
treated application. Therefore, we think the system may be used or adapted
easily to different case studies. We focus here on a first step in the
decision-support process which concerns the modeling of information issued from
the perceived environment and their representation dynamically using a
multiagent system. This modeling was applied on the RoboCupRescue Simulation
System. An implementation and some results are presented here.Comment:
Combination interventions for Hepatitis C and Cirrhosis reduction among people who inject drugs: An agent-based, networked population simulation experiment
Hepatitis C virus (HCV) infection is endemic in people who inject drugs
(PWID), with prevalence estimates above 60 percent for PWID in the United
States. Previous modeling studies suggest that direct acting antiviral (DAA)
treatment can lower overall prevalence in this population, but treatment is
often delayed until the onset of advanced liver disease (fibrosis stage 3 or
later) due to cost. Lower cost interventions featuring syringe access (SA) and
medically assisted treatment (MAT) for addiction are known to be less costly,
but have shown mixed results in lowering HCV rates below current levels. Little
is known about the potential synergistic effects of combining DAA and MAT
treatment, and large-scale tests of combined interventions are rare. While
simulation experiments can reveal likely long-term effects, most prior
simulations have been performed on closed populations of model agents--a
scenario quite different from the open, mobile populations known to most health
agencies. This paper uses data from the Centers for Disease Control's National
HIV Behavioral Surveillance project, IDU round 3, collected in New York City in
2012 by the New York City Department of Health and Mental Hygiene to
parameterize simulations of open populations. Our results show that, in an open
population, SA/MAT by itself has only small effects on HCV prevalence, while
DAA treatment by itself can significantly lower both HCV and HCV-related
advanced liver disease prevalence. More importantly, the simulation experiments
suggest that cost effective synergistic combinations of the two strategies can
dramatically reduce HCV incidence. We conclude that adopting SA/MAT
implementations alongside DAA interventions can play a critical role in
reducing the long-term consequences of ongoing infection
Developing an agent-based simulation model of software evolution
Context In attempt to simulate the factors that affect the software evolution behaviour and possibly predict it, several simulation models have been developed recently. The current system dynamic (SD) simulation model of software evolution process was built based on actor-network theory (ANT) of software evolution by using system dynamic environment, which is not a suitable environment to reflect the complexity of ANT theory. In addition the SD model has not been investigated for its ability to represent the real-world process of software evolution. Objectives This paper aims to re-implements the current SD model to an agent-based simulation environment ‘Repast’ and checks the behaviour of the new model compared to the existing SD model. It also aims to investigate the ability of the new Repast model to represent the real-world process of software evolution. Methods a new agent-based simulation model is developed based on the current SD model's specifications and then tests similar to the previous model tests are conducted in order to perform a comparative evaluation between of these two results. In addition an investigation is carried out through an interview with an expert in software development area to investigate the model's ability to represent real-world process of software evolution. Results The Repast model shows more stable behaviour compared with the SD model. Results also found that the evolution health of the software can be calibrated quantitatively and that the new Repast model does have the ability to represent real-world processes of software evolution. Conclusion It is concluded that by applying a more suitable simulation environment (agent-based) to represent ANT theory of software evolution, that this new simulation model will show more stable bahaviour compared with the previous SD model; And it will also shows the ability to represent (at least quantatively) the real-world aspect of software evolution.Peer reviewedFinal Accepted Versio
Towards Social Autonomous Vehicles: Efficient Collision Avoidance Scheme Using Richardson's Arms Race Model
Background Road collisions and casualties pose a serious threat to commuters
around the globe. Autonomous Vehicles (AVs) aim to make the use of technology
to reduce the road accidents. However, the most of research work in the context
of collision avoidance has been performed to address, separately, the rear end,
front end and lateral collisions in less congested and with high
inter-vehicular distances. Purpose The goal of this paper is to introduce the
concept of a social agent, which interact with other AVs in social manners like
humans are social having the capability of predicting intentions, i.e.
mentalizing and copying the actions of each other, i.e. mirroring. The proposed
social agent is based on a human-brain inspired mentalizing and mirroring
capabilities and has been modelled for collision detection and avoidance under
congested urban road traffic.
Method We designed our social agent having the capabilities of mentalizing
and mirroring and for this purpose we utilized Exploratory Agent Based Modeling
(EABM) level of Cognitive Agent Based Computing (CABC) framework proposed by
Niazi and Hussain.
Results Our simulation and practical experiments reveal that by embedding
Richardson's arms race model within AVs, collisions can be avoided while
travelling on congested urban roads in a flock like topologies. The performance
of the proposed social agent has been compared at two different levels.Comment: 48 pages, 21 figure
Towards the Development of a Simulator for Investigating the Impact of People Management Practices on Retail Performance
Often models for understanding the impact of management practices on retail
performance are developed under the assumption of stability, equilibrium and
linearity, whereas retail operations are considered in reality to be dynamic,
non-linear and complex. Alternatively, discrete event and agent-based modelling
are approaches that allow the development of simulation models of heterogeneous
non-equilibrium systems for testing out different scenarios. When developing
simulation models one has to abstract and simplify from the real world, which
means that one has to try and capture the 'essence' of the system required for
developing a representation of the mechanisms that drive the progression in the
real system. Simulation models can be developed at different levels of
abstraction. To know the appropriate level of abstraction for a specific
application is often more of an art than a science. We have developed a retail
branch simulation model to investigate which level of model accuracy is
required for such a model to obtain meaningful results for practitioners.Comment: 24 pages, 7 figures, 6 tables, Journal of Simulation 201
- …