Agent-Based Computational Modelling: An Introduction

Author(s):  
Francesco C. Billari ◽  
Thomas Fent ◽  
Alexia Prskawetz ◽  
Jürgen Scheffran
PLoS ONE ◽  
2021 ◽  
Vol 16 (7) ◽  
pp. e0254763
Author(s):  
Joel Dokmegang ◽  
Moi Hoon Yap ◽  
Liangxiu Han ◽  
Matteo Cavaliere ◽  
René Doursat

Understanding the processes by which the mammalian embryo implants in the maternal uterus is a long-standing challenge in embryology. New insights into this morphogenetic event could be of great importance in helping, for example, to reduce human infertility. During implantation the blastocyst, composed of epiblast, trophectoderm and primitive endoderm, undergoes significant remodelling from an oval ball to an egg cylinder. A main feature of this transformation is symmetry breaking and reshaping of the epiblast into a “cup”. Based on previous studies, we hypothesise that this event is the result of mechanical constraints originating from the trophectoderm, which is also significantly transformed during this process. In order to investigate this hypothesis we propose MG# (MechanoGenetic Sharp), an original computational model of biomechanics able to reproduce key cell shape changes and tissue level behaviours in silico. With this model, we simulate epiblast and trophectoderm morphogenesis during implantation. First, our results uphold experimental findings that repulsion at the apical surface of the epiblast is essential to drive lumenogenesis. Then, we provide new theoretical evidence that trophectoderm morphogenesis indeed can dictate the cup shape of the epiblast and fosters its movement towards the uterine tissue. Our results offer novel mechanical insights into mouse peri-implantation and highlight the usefulness of agent-based modelling methods in the study of embryogenesis.


2018 ◽  
Vol 53 (9) ◽  
pp. 560-569 ◽  
Author(s):  
Adam Hulme ◽  
Jason Thompson ◽  
Rasmus Oestergaard Nielsen ◽  
Gemma J M Read ◽  
Paul M Salmon

ObjectivesThere have been recent calls for the application of the complex systems approach in sports injury research. However, beyond theoretical description and static models of complexity, little progress has been made towards formalising this approach in way that is practical to sports injury scientists and clinicians. Therefore, our objective was to use a computational modelling method and develop a dynamic simulation in sports injury research.MethodsAgent-based modelling (ABM) was used to model the occurrence of sports injury in a synthetic athlete population. The ABM was developed based on sports injury causal frameworks and was applied in the context of distance running-related injury (RRI). Using the acute:chronic workload ratio (ACWR), we simulated the dynamic relationship between changes in weekly running distance and RRI through the manipulation of various ‘athlete management tools’.ResultsThe findings confirmed that building weekly running distances over time, even within the reported ACWR ‘sweet spot’, will eventually result in RRI as athletes reach and surpass their individual physical workload limits. Introducing training-related error into the simulation and the modelling of a ‘hard ceiling’ dynamic resulted in a higher RRI incidence proportion across the population at higher absolute workloads.ConclusionsThe presented simulation offers a practical starting point to further apply more sophisticated computational models that can account for the complex nature of sports injury aetiology. Alongside traditional forms of scientific inquiry, the use of ABM and other simulation-based techniques could be considered as a complementary and alternative methodological approach in sports injury research.


2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Dale Richards

PurposeThe ability for an organisation to adapt and respond to external pressures is a beneficial activity towards optimising efficiency and increasing the likelihood of achieving set goals. It can also be suggested that this very ability to adapt to one's surroundings is one of the key factors of resilience. The nature of dynamically responding to sudden change and then to return to a state that is efficient may be termed as possessing the characteristic of plasticity. Uses of agent-based systems in assisting in organisational processes may have a hand in facilitating an organisations' plasticity, and computational modelling has often been used to try and predict both agent and human behaviour. Such models also promise the ability to examine the dynamics of organisational plasticity through the direct manipulation of key factors. This paper discusses the use of such models in application to organisational plasticity and in particular the relevance to human behaviour and perception of agent-based modelling. The uses of analogies for explaining organisational plasticity is also discussed, with particular discussion around the use of modelling. When the authors consider the means by which the authors can adopt theories to explain this type of behaviour, models tend to focus on aspects of predictability. This in turn loses a degree of realism when we consider the complex nature of human behaviour, and more so that of human–agent behaviour.Design/methodology/approachThe methodology and approach used for this paper is reflected in the review of the literature and research.FindingsThe use of human–agent behaviour models in organisational plasticity is discussed in this paper.Originality/valueThe originality of this paper is based on the importance of considering the human–agent-based models. When compared to agent-based model approaches, analogy is used as a narrative in this paper.


2012 ◽  
Vol 9 (72) ◽  
pp. 1576-1588 ◽  
Author(s):  
Michelle L. Wynn ◽  
Paul M. Kulesa ◽  
Santiago Schnell

Follow-the-leader chain migration is a striking cell migratory behaviour observed during vertebrate development, adult neurogenesis and cancer metastasis. Although cell–cell contact and extracellular matrix (ECM) cues have been proposed to promote this phenomenon, mechanisms that underlie chain migration persistence remain unclear. Here, we developed a quantitative agent-based modelling framework to test mechanistic hypotheses of chain migration persistence. We defined chain migration and its persistence based on evidence from the highly migratory neural crest model system, where cells within a chain extend and retract filopodia in short-lived cell contacts and move together as a collective. In our agent-based simulations, we began with a set of agents arranged as a chain and systematically probed the influence of model parameters to identify factors critical to the maintenance of the chain migration pattern. We discovered that chain migration persistence requires a high degree of directional bias in both lead and follower cells towards the target. Chain migration persistence was also promoted when lead cells maintained cell contact with followers, but not vice-versa. Finally, providing a path of least resistance in the ECM was not sufficient alone to drive chain persistence. Our results indicate that chain migration persistence depends on the interplay of directional cell movement and biased cell–cell contact.


2019 ◽  
Vol 8 ◽  
pp. 1-26
Author(s):  
Eli Nomes ◽  
André Grow ◽  
Jan Van Bavel

Around the middle of the 20th century, most Western countries experienced a surge in birth rates, called the Baby Boom. This boom was unexpected at the time and the underlying mechanisms are still not entirely clear. It was characterized by high levels of inter- and intra-country variability in fertility, as some regions even experienced fertility decline during the Boom. In this paper, we suggest that social influence processes, propelling a shift towards two-child families, might have played an important role in the observed changes in fertility. Interactions in social networks can lead new types of childbearing behaviour to diffuse widely and thereby induce changes in fertility at the macro level. The emergence and diffusion of a two-child norm resulted in homogenization of fertility behaviour across regions. Overall, this led to a reduction of childlessness and thus an increase of fertility, as more people aspired to have at least two children. Yet, in those regions where larger family sizes were still common, the two-child norm contributed to a fertility decline. To explore the role of social influence with analytical rigor, we make use of agent-based computational modelling. We explicate the underlying behavioural assumptions in a formal model and assess their implications by submitting this model to computational simulation experiments. We use Belgium as a case study, since it exhibited large variability in fertility in a relatively small population during the Baby Boom years. We use census data to generate realistic starting conditions and to empirically validate the outcomes that our model generates. Our results show that the proposed mechanism could explain an important part of the variability of fertility trends during the Baby Boom era.


2020 ◽  
Author(s):  
Elizabeth Hunter ◽  
John Kelleher

Abstract BackgroundIn order to be prepared for an infectious disease outbreak it is important to know what interventions will or will not have an impact on reducing the outbreak. While some interventions might have a greater effect in mitigating an outbreak, others might only have a minor effect but all interventions will have a cost in implementation. Estimating the effectiveness of an intervention can be done using computational modelling. In particular, comparing the results of model runs with an intervention in place to control runs where no interventions were used can help to determine what interventions will have the greatest effect on an outbreak. MethodsTo test the effects of a school closure policy on the spread of an infectious disease (in this case measles) we run simulations closing schools based on either the proximity of the town to the initial outbreak or the centrality of the town within the network of towns in the simulation. To do this we use a hybrid model that combines an agent-based model with an equation-based model. ResultsOur results show that closing down the schools in the town where an outbreak begins and the town with the highest in degree centrality provides the largest reduction in percent of runs leading to an outbreak as well as a reduction in the overall size of the outbreak compared to only closing down the town where the outbreak begins. Although closing down schools in the town with the closest proximity to the town where the outbreak begins also provides a reduction in the chance of an outbreak, we do not find the reduction to be as large as when the schools in the high in degree centrality town are closed. ConclusionsThus we believe that focusing on high in degree centrality towns during an outbreak is important in reducing the overall size of an outbreak.


Author(s):  
Jithender J. Timothy ◽  
Vijaya Holla ◽  
Günther Meschke

We analyse the dynamics of COVID-19 using computational modelling at multiple scales. For large scale analysis, we propose a 2-scale lattice extension of the classical SIR-type compartmental model with spatial interactions called the Lattice-SIRQL model. Computational simulations show that global quantifiers are not completely representative of the actual dynamics of the disease especially when mitigation measures such as quarantine and lockdown are applied. Furthermore, using real data of confirmed COVID-19 cases, we calibrate the Lattice-SIRQL model for 105 countries. The calibrated model is used to make country specific recommendations for lockdown relaxation and lockdown continuation. Finally, using an agent-based model we analyse the influence of cluster level relaxation rate and lockdown duration on disease spreading.


2021 ◽  
Vol 48 (1) ◽  
pp. 65-74
Author(s):  
Nova Asriana

Agent-based modelling is an approach to develop a design strategy in socio-related studies to understand pedestrian behavior by using simulation through validation using field observation. This study area has a historic city so that having several potential advantages as destination tourists and also having urban issues. Some facilities disseminate prosperous for domestic tourist destinations, transportation hubs (land and water-based transport), and public facilities. The purpose is to develop a design strategy of pedestrian behavior in urban space to be procedure based on computational modelling. By merging the result, it helps designers to depict pedestrian movement flow, permeability, and connectivity patterns, which represent the presumptions of the origins or source of movement, destinations, generators, and attractors of movement. This simulation examines and valuates spatial behavior models allowing to route preferences of each pedestrian in order to be used in the strategy of design process for architect, urban planner, or other designer stakeholders. The result will imply a walkable pedestrian-way design, where this approach of a pedestrian experience might be an effective tool in city planning.


2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Elizabeth Hunter ◽  
John D. Kelleher

Abstract Background In order to be prepared for an infectious disease outbreak it is important to know what interventions will or will not have an impact on reducing the outbreak. While some interventions might have a greater effect in mitigating an outbreak, others might only have a minor effect but all interventions will have a cost in implementation. Estimating the effectiveness of an intervention can be done using computational modelling. In particular, comparing the results of model runs with an intervention in place to control runs where no interventions were used can help to determine what interventions will have the greatest effect on an outbreak. Methods To test the effects of a school closure policy on the spread of an infectious disease (in this case measles) we run simulations closing schools based on either the proximity of the town to the initial outbreak or the centrality of the town within the network of towns in the simulation. To do this we use a hybrid model that combines an agent-based model with an equation-based model. In our analysis, we use three measures to compare the effects of different intervention strategies: the total number of model runs leading to an outbreak, the total number of infected agents, and the geographic spread of outbreaks. Results Our results show that closing down the schools in the town where an outbreak begins and the town with the highest in degree centrality provides the largest reduction in percent of runs leading to an outbreak as well as a reduction in the geographic spread of the outbreak compared to only closing down the town where the outbreak begins. Although closing down schools in the town with the closest proximity to the town where the outbreak begins also provides a reduction in the chance of an outbreak, we do not find the reduction to be as large as when the schools in the high in degree centrality town are closed. Conclusions Thus we believe that focusing on high in degree centrality towns during an outbreak is important in reducing the overall size of an outbreak.


2021 ◽  
Vol 127 ◽  
pp. 01014
Author(s):  
Alexander Ioilyevich Ilyinsky ◽  
Galina Vladimirovna Klimova ◽  
Evgeniy Sergeevich Smakhtin ◽  
Marina Aleksandrovna Amurskaya ◽  
Ekaterina Yurievna Rozhina

The article describes approaches to applying agent-based modelling and, particularly, the case of Naming Game, in linguistic studies and within teaching foreign languages. Computational modelling implementation has become a comprehensive and ambitious field of research, as its methods are applicable to solving tasks set within various aspects of contemporary society and science. The main purpose of this paper is to perform an analysis of Naming Game implementation in language emergence and evolution studies. To achieve this purpose we set several tasks: to present a vast literature review on agent-based modelling in linguistics and other adjacent sciences; to give an overview and description of the Naming Game; to perform simulations within the Naming Game and present their outcomes. As the main methodology the article uses simulations. The paper concludes that a clear hysteresis effect is present in the dependence of the size of the population vocabulary from the size of vocabulary of its average agent. At the point where the population vocabulary transitions into the uniform distribution the average agent’s vocabulary reaches saturation and plateaus. Those dynamics also change as the population vocabulary grows and declines. Agent-based modelling is a relatively novel direction for linguistics with a modest number of research papers. Results, presented in the paper, give a fresh angle on the issues of language emergence and evolution.


Sign in / Sign up

Export Citation Format

Share Document