17,691 research outputs found
Simulating acculturation dynamics between migrants and locals in relation to network formation
International migration implies the coexistence of different ethnic and
cultural groups in the receiving country. The refugee crisis of 2015 has
resulted in critical levels of opinion polarization on the question of whether
to welcome migrants, causing clashes in receiving countries. This scenario
emphasizes the need to better understand the dynamics of mutual adaptation
between locals and migrants, and the conditions that favor successful
integration. Agent-based simulations can help achieve this goal. In this work,
we introduce our model MigrAgent and our preliminary results. The model
synthesizes the dynamics of migration intake and post-migration adaptation. It
explores the different acculturation outcomes that can emerge from the mutual
adaptation of a migrant population and a local population depending on their
degree of tolerance. With parameter sweeping, we detect how different
acculturation strategies can coexist in a society and in different degrees
among various subgroups. The results show higher polarization effects between a
local population and a migrant population for fast intake conditions. When
migrant intake is slow, transitory conditions between acculturation outcomes
emerge for subgroups, e.g., from assimilation to integration for liberal
migrants and from marginalization to separation for conservative migrants.
Relative group sizes due to speed of intake cause counterintuitive scenarios,
such as the separation of liberal locals. We qualitatively compare the
processes of our model with the German portion sample of the survey Causes and
Consequences of Socio-Cultural Integration Processes among New Immigrants in
Europe (SCIP), finding preliminary confirmation of our assumptions and results.Comment: 24 pages, plus supplemental material, 11 figure
A multi-agent system approach in evaluating human spatio-temporal vulnerability to seismic risk using social attachment
International audienceSocial attachment theory states that individuals seek the proximity of attachment figures (e.g. family members, friends, colleagues, familiar places or objects) when faced with threat. During disasters, this means that family members may seek each other before evacuating, gather personal property before heading to familiar exits and places, or follow groups/crowds, etc. This hard-wired human tendency should be considered in the assessment of risk and the creation of disaster management plans. Doing so may result in more realistic evacuation procedures and may minimise the number of casualties and injuries. In this context, a dynamic spatio-temporal analysis of seismic risk is presented using SOLACE, a multi-agent model of pedestrian behaviour based on social attachment theory implemented using the Belief-Desire-Intention approach. The model focuses on the influence of human, social, physical and temporal factors on successful evacuation. Human factors considered include perception and mobility defined by age. Social factors are defined by attachment bonds, social groups, population distribution, and cultural norms. Physical factors refer to the location of the epicentre of the earthquake, spatial distribution/layout and attributes of environmental objects such as buildings, roads, barriers (cars), placement of safe areas, evacuation routes, and the resulting debris/damage from the earthquake. Experiments tested the influence of time of the day, presence of disabled persons and earthquake intensity. Initial results show that factors that influence arrivals in safe areas include (a) human factors (age, disability, speed), (b) pre-evacuation behaviours, (c) perception distance (social attachment, time of day), (d) social interaction during evacuation, and (e) physical and spatial aspects, such as limitations imposed by debris (damage), and the distance to safe areas. To validate the results, scenarios will be designed with stakeholders, who will also take part in the definition of a serious game. The recommendation of this research is that both social and physical aspects should be considered when defining vulnerability in the analysis of risk
Agent-based Analysis of the Spread of Awareness in the Population in the Prodromal Phase of Bushfires
Efficient communication is essential in disasters in order to coordinate a response and assure effective evacuation. This paper focuses on the case study of the Melbourne bushfires in 2009. We first analysed some interviews of the population to know who the population communicates with (neighbours, family, authorities, etc), and using what channel (radio, phone, internet, etc). We then developed and implemented communicative actions in a Belief-Desire-Intention model of the population\u27s behaviour. Finally, we ran experiments in order to compare the speed at which the population becomes aware of the fires in different scenarios with different types of communication (more or less organised). Our first results show that more organised modes of communication would provide significant benefits in terms of propagation of awareness in the population
Investigation of Pre-evacuation and Wayfinding Behaviors Impacts using Agent-Based Simulation for Smart Evacuation Technology.
Despite significant safety improvements, the mining industry remains one of the most hazardous occupations globally and the evacuation of Miners, when an uncontrollable incident occurs in the mine, is the best bet to saving lives. However, Human factors/behaviors during an emergency are likely to influence the evacuation performance. Other industries have made a significant effort to determine these human factors that can impede evacuation performance, however, the current state-of-the-art in mine evacuation or self-rescue is that the evacuation route is predetermined, and a static sign is used to direct miners to the predetermined safe location. This method is limited in representing actual conditions that arise in a real emergency, neglecting the different behaviors displayed by humans. As optimization of the evacuation of a mine plays a fundamental role in emergencies and modelling evacuation behavior and movement of miners is a complex task, this research utilized Agent-Based simulations to simulate the evacuation behavior and performance. It was observed that people with the smart evacuation device made evacuated faster than the passive signage scenario and chaotic scenario. It is imperative to consider the impact of pre-evacuation and wayfinding behavior of people when designing the evacuation protocols
Complex networks analysis in socioeconomic models
This chapter aims at reviewing complex networks models and methods that were
either developed for or applied to socioeconomic issues, and pertinent to the
theme of New Economic Geography. After an introduction to the foundations of
the field of complex networks, the present summary adds insights on the
statistical mechanical approach, and on the most relevant computational aspects
for the treatment of these systems. As the most frequently used model for
interacting agent-based systems, a brief description of the statistical
mechanics of the classical Ising model on regular lattices, together with
recent extensions of the same model on small-world Watts-Strogatz and
scale-free Albert-Barabasi complex networks is included. Other sections of the
chapter are devoted to applications of complex networks to economics, finance,
spreading of innovations, and regional trade and developments. The chapter also
reviews results involving applications of complex networks to other relevant
socioeconomic issues, including results for opinion and citation networks.
Finally, some avenues for future research are introduced before summarizing the
main conclusions of the chapter.Comment: 39 pages, 185 references, (not final version of) a chapter prepared
for Complexity and Geographical Economics - Topics and Tools, P.
Commendatore, S.S. Kayam and I. Kubin Eds. (Springer, to be published
Complex network analysis and nonlinear dynamics
This chapter aims at reviewing complex network and nonlinear dynamical
models and methods that were either developed for or applied to socioeconomic
issues, and pertinent to the theme of New Economic Geography. After an introduction
to the foundations of the field of complex networks, the present summary
introduces some applications of complex networks to economics, finance, epidemic
spreading of innovations, and regional trade and developments. The chapter also
reviews results involving applications of complex networks to other relevant
socioeconomic issue
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