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Modelling
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Agent-Based Modelling
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Agent-Based Modelling

A special issue of Modelling (ISSN 2673-3951).

Deadline for manuscript submissions: closed (30 September 2021) | Viewed by 21447

Special Issue Editors

Prof. Dr. José Manuel Galán

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Guest Editor
INSISOC, Área de Organización de Empresas, Departamento de Ingeniería de Organización, Escuela Politécnica Superior, Universidad de Burgos, Campus Río Vena, Avda. Cantabria s/n 09006 Burgos, Spain
Interests: agent-based modeling; complex networks; machine learning
Dr. José Ignacio Santos

E-Mail Website
Guest Editor
INSISOC, Área de Organización de Empresas, Departamento de Ingeniería de Organización, Escuela Politécnica Superior, Universidad de Burgos, Campus Río Vena, Avda. Cantabria s/n 09006 Burgos, Spain
Interests: agent-based modeling; complex networks; machine learning
Dr. Rubén Fuentes-Fernández

E-Mail Website
Guest Editor
GRASIA (Research Group on Agent-based, Social & Interdisciplinary Applications), Department of Software Engineering and Artificial Intelligence, Facultad de Informática, Universidad Complutense de Madrid, Facultad de Informática, Universidad Complutense de Madrid, Calle Profesor José García Santesmases 9, Madrid 28040, Spain
Interests: intelligent agents; model-driven engineering of collaborative systems; e-learning; ambient intelligence; bioinformatics, accessibility, and inclusion

Special Issue Information

Dear Colleagues,

In the last 30 years, agent-based modeling (ABM) and related similar approaches with different nuances and names (e.g., agent-based systems (ABSs), individual-based modeling (IBM), multi-agent systems (MASs), or multi-agent-based simulations (MABSs)) have shifted from being a heterodox modeling approach to become a recognized research methodology, in many cases one of the mainstream modeling techniques, in a wide range of scientific disciplines.

In an agent-based model, the individuals or entities that participate in a system under study and the interactions between them and with the environment are explicitly modeled as computational agents and interactions. This modeling approach presents important advantages, since it facilitates the abstraction of complex systems, the integration of spatial elements, including heterogeneity in the representation, and enables the use of computers as an inference engine. However, it also entails some problems such as the use of induction for the generalization of results, the verification and validation of the models, or the reuse of code and scalability.

This Special Issue not only aims to advance the methodological elements of the modeling process using agent technologies, but also to showcase rigorous uses of theoretical and empirical ABM in different applied domains and disciplines.

Prof. Dr. José Manuel Galán
Dr. José Ignacio Santos
Dr. Ruben Fuentes-Fernández
Guest Editors

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Modelling is an international peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Agent-based modeling and simulation (ABMS)
  • Multi-agent systems (MASs)
  • Model
  • Simulation
  • Methodology
  • Case study

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Published Papers (5 papers)

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11 pages, 665 KiB  
Article
Estimating the Benefits of Korea’s Intercity Rail Speed Increase Project: An Agent-Based Model Approach
by Chansung Kim, Heesub Rim, DongIk Oh and Dongwoon Kang
Modelling 2022, 3(1), 94-104; https://doi.org/10.3390/modelling3010007 - 30 Jan 2022
Cited by 2 | Viewed by 3002
Abstract
In the cost–benefit analysis of urban transportation investment, a logsum-based benefit calculation is widely used. However, it is rarely applied to inter-regional transportation. In this study, we applied a logsum-based approach to the calculation of benefits for high-speed projects for inter-regional railways in [...] Read more.
In the cost–benefit analysis of urban transportation investment, a logsum-based benefit calculation is widely used. However, it is rarely applied to inter-regional transportation. In this study, we applied a logsum-based approach to the calculation of benefits for high-speed projects for inter-regional railways in Korea’s long-term transportation plan. Moreover, we applied a behavioral model in which an agent travels beyond the zones assumed by an aggregate model. In the case of South Korea, such a model is important for determining transportation priorities: whether to specialize in mobility improvement by investing in a high-speed railway project, such as the 300 km/h Korea Train eXpress (KTX), or to improve existing facilities, such as by building a relatively slower railroad (150–250 km/h) to enhance existing mobility and accessibility. In this context, if a new, relatively slow railroad were constructed adjacent to a high-speed railroad, the benefits would be negligible since the reduction in travel time would not sufficiently reflect accessibility improvements. Therefore, this study proposes the use of aggregate and agent-based models to evaluate projects to improve intercity railway service and conduct a case study with the proposed new methodology. A logsum was selected to account for the benefits of passenger cars on semi-high-speed and high-speed railroads simultaneously since it has been widely used to estimate the benefits of new modes or relatively slow modes. To calculate the logsum, this study used input data from both the aggregate and individual agent-based models, and found that an analysis of the feasibility of inter-regional railroad investment was possible. Moreover, the agent-based model can also be applied to inter-regional analysis. The proposed methods are expected to enable a more comprehensive evaluation of the transport system. In the case of the agent-based model, it is suggested that further studies undertake more detailed scenario analysis and travel time estimation. Full article
(This article belongs to the Special Issue Agent-Based Modelling)
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23 pages, 1567 KiB  
Article
Interactive Agent-Based Simulation for Experimentation: A Case Study with Cooperative Game Theory
by Andrew J. Collins and Sheida Etemadidavan
Modelling 2021, 2(4), 425-447; https://doi.org/10.3390/modelling2040023 - 29 Sep 2021
Cited by 9 | Viewed by 4965
Abstract
Incorporating human behavior is a current challenge for agent-based modeling and simulation (ABMS). Human behavior includes many different aspects depending on the scenario considered. The scenario context of this paper is strategic coalition formation, which is traditionally modeled using cooperative game theory, but [...] Read more.
Incorporating human behavior is a current challenge for agent-based modeling and simulation (ABMS). Human behavior includes many different aspects depending on the scenario considered. The scenario context of this paper is strategic coalition formation, which is traditionally modeled using cooperative game theory, but we use ABMS instead; as such, it needs to be validated. One approach to validation is to compare the recorded behavior of humans to what was observed in our simulation. We suggest that using an interactive simulation is a good approach to collecting the necessary human behavior data because the humans would be playing in precisely the same context as the computerized agents. However, such a validation approach may be suspectable to extraneous effects. In this paper, we conducted a correlation research experiment that included an investigation into whether game theory experience, an extraneous variable, affects human behavior in our interactive simulation; our results indicate that it did not make a significant difference. However, in only 42 percent of the trials did the human participants’ behavior result in an outcome predicted by the underlying theory used in our model, i.e., cooperative game theory. This paper also provides a detailed case study for creating an interactive simulation for experimentation. Full article
(This article belongs to the Special Issue Agent-Based Modelling)
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21 pages, 41638 KiB  
Article
Consideration of Complexity in the Management of Construction and Demolition Waste Flow in French Regions: An Agent-Based Computational Economics Approach
by Fenintsoa Andriamasinoro and Daniel Monfort-Climent
Modelling 2021, 2(3), 385-405; https://doi.org/10.3390/modelling2030021 - 25 Aug 2021
Cited by 2 | Viewed by 3159
Abstract
For each region of France, there is currently a program to implement a plan for regional prevention and management of construction and demolition waste (CDW) used in the buildings and public works (e.g., roads) sector, also called the BTP (from the French Bâtiment [...] Read more.
For each region of France, there is currently a program to implement a plan for regional prevention and management of construction and demolition waste (CDW) used in the buildings and public works (e.g., roads) sector, also called the BTP (from the French Bâtiment et Travaux Publics) sector. To implement such a plan, its complexity must be considered; i.e., account (a) for how different scales are endogenously connected and (b) for decision-making rules at each scale being introduced. However, this complexity has rarely been taken into account in the literature. Using the PACA region as a case-study, this paper presents the first results of modelling that determines a hypotheses for the geographic distribution of the road renovation rate in each municipality (microscale) and Department (mesoscale) in a region of France. Such a renovation requires recycled aggregates (gravel) and asphalt supplies simultaneously. To consider this endogenous connection between scales, the model at the micro-scale must also be calibrated so the simulated values emerging at a higher-scale approach a supply–demand balance. We also discuss the transposition of the model to another French region (Ile-de-France). The method we used is the Agent-based Computational Economics (ACE) modelling approach. In addition, the coherent interplay between scales is determined by an approach called pattern-oriented modelling (POM). Our research revealed, at a thematic level, that for a circular economy to develop, the network of facilities in the territory is very important, and effective commercialization of secondary resources is major in the areas that group together recycling platforms and nearby asphalt plants. At a methodological level, our research revealed that in any multi-level modelling exercise, POM can be seen as an essential approach to accompany the ACE approach, particularly for a macroeconomic (here macro = regional) looping of a model designed at a microscale. However, convincing the BTP sector to integrate ACE/POM as a full part of a methodological support for regional prevention and management of CDW remains a challenge Full article
(This article belongs to the Special Issue Agent-Based Modelling)
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31 pages, 5610 KiB  
Article
A Statistical Examination of Distinct Characteristics Influencing the Performance of Vector-Borne Epidemiological Agent-Based Simulation Models
by Anna Paula Galvão Scheidegger, Henrique dos Santos Maxir and Amarnath Banerjee
Modelling 2021, 2(2), 166-196; https://doi.org/10.3390/modelling2020009 - 24 Mar 2021
Cited by 1 | Viewed by 2893
Abstract
The spread of infectious diseases is a complex system in which pathogens, humans, the environment, and sometimes vectors interact. Mathematical and simulation modelling is a suitable approach to investigate the dynamics of such complex systems. The 2019 novel coronavirus (COVID-19) pandemic reinforced the [...] Read more.
The spread of infectious diseases is a complex system in which pathogens, humans, the environment, and sometimes vectors interact. Mathematical and simulation modelling is a suitable approach to investigate the dynamics of such complex systems. The 2019 novel coronavirus (COVID-19) pandemic reinforced the importance of agent-based simulation models to quickly and accurately provide information about the disease spread that would be otherwise hard or risky to obtain, and how this information can be used to support infectious disease control decisions. Due to the trade-offs between complexity, time, and accuracy, many assumptions are frequently made in epidemiological models. With respect to vector-borne diseases, these assumptions lead to epidemiological models that are usually bounded to single-strain and single-vector scenarios, where human behavior is modeled in a simplistic manner or ignored, and where data quality is usually not evaluated. In order to leverage these models from theoretical tools to decision-making support tools, it is important to understand how information quality, human behavior, multi-vector, and multi-strain affect the results. For this, an agent-based simulation model with different parameter values and different scenarios was considered. Its results were compared with the results of a traditional compartmental model with respect to three outputs: total number of infected individuals, duration of the epidemic, and number of epidemic waves. Paired t-test showed that, in most cases, data quality, human behavior, multi-vector, and multi-strain were characteristics that lead to statistically different results, while the computational costs to consider them were not high. Therefore, these characteristics should be investigated in more detail and be accounted for in epidemiological models in order to obtain more reliable results that can assist the decision-making process during epidemics. Full article
(This article belongs to the Special Issue Agent-Based Modelling)
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16 pages, 1485 KiB  
Systematic Review
A Literature Review of Hybrid System Dynamics and Agent-Based Modeling in a Produced Water Management Context
by Saeed P. Langarudi, Robert P. Sabie, Babak Bahaddin and Alexander G. Fernald
Modelling 2021, 2(2), 224-239; https://doi.org/10.3390/modelling2020012 - 9 Apr 2021
Cited by 8 | Viewed by 3795
Abstract
This paper explores the possibility and plausibility of developing a hybrid simulation method combining agent-based (AB) and system dynamics (SD) modeling to address the case study of produced water management (PWM). In southeastern New Mexico, the oil and gas industry generates large volumes [...] Read more.
This paper explores the possibility and plausibility of developing a hybrid simulation method combining agent-based (AB) and system dynamics (SD) modeling to address the case study of produced water management (PWM). In southeastern New Mexico, the oil and gas industry generates large volumes of produced water, while at the same time, freshwater resources are scarce. Single-method models are unable to capture the dynamic impacts of PWM on the water budget at both the local and regional levels, hence the need for a more complex hybrid approach. We used the literature, information characterizing produced water in New Mexico, and our preliminary interviews with subject matter experts to develop this framework. We then conducted a systematic literature review to summarize state-of-the-art of hybrid modeling methodologies and techniques. Our research revealed that there is a small but growing volume of hybrid modeling research that could provide some foundational support for modelers interested in hybrid modeling approaches for complex natural resource management issues. We categorized these efforts into four classes based on their approaches to hybrid modeling. It appears that, among these classes, PWM requires the most sophisticated approach, indicating that PWM modelers will need to face serious challenges and break new ground in this realm. Full article
(This article belongs to the Special Issue Agent-Based Modelling)
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