An Agent-Based Model for Simulating Irrigated Agriculture in the Samambaia Basin in Goiás

Agriculture is one of the main economic activities in Brazil. The intensive use of water for irrigated agriculture leads to water rise demand contributing to increase water stress. Agent-based models help assess this problem with promising applications entailing an organizing principle to inform us of how to view a real-world system and effectively build a model. In this work, agent-based modeling is applied to simulate water usage for irrigation in agricultural production in the Samambaia river basin in the municipality of Cristalina in the Goias state of Brazil. The use of real data enables analysis of resource availability in a scenario with high demand irrigation, allowing a greater understanding of the needs of the parties involved.

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Exploring the dynamics of neighborhood ethnic segregation with agent-based modelling: an empirical application to Bradford

10.31235/osf.io/gmzdp ◽

2021 ◽

Author(s):

Carolina Zuccotti ◽

Jan Lorenz ◽

Rocco Paolillo ◽

Alejandra Rodríguez Sánchez ◽

Selamavit Serka

Keyword(s):

Real Data ◽

Agent Based Modeling ◽

Residential Choice ◽

Ethnic Segregation ◽

Agent Based ◽

Schelling Model ◽

Residential Moves ◽

Micro Level ◽

The Uk

How individuals’ residential moves in space—derived from their varied preferences and constraints—translate into the overall segregation patterns that we observe, remains a key challenge in neighborhood ethnic segregation research. In this paper we use agent-based modeling to explore this concern, focusing on the interactive role of ethnic and socio-economic homophily preferences and housing constraints as determinants of residential choice. Specifically, we extend the notorious Schelling’s model to a random utility discrete choice approach to simulate the relocation decision of people (micro level) and how they translate into spatial segregation outcomes (macro level). We model different weights for preferences of ethnic and socioeconomic similarity in neighborhood composition over random relocations, in addition to housing constraints. We formalize how different combinations of these variables could replicate real segregation scenarios in Bradford, a substantially segregated local authority in the UK. We initialize our model with geo-referenced data from the 2011 Census and use Dissimilarity and the Average Local Simpson Indices as measures of segregation. As in the original Schelling model, the simulation shows that even mild preferences to reside close to co-ethnics can lead to high segregation levels. Nevertheless, ethnic over-segregation decreases, and results come close to real data, when preferences for socioeconomic similarity are slightly above preferences for ethnic similarity, and even more so when housing constraints are considered in relocation moves of agents. We discuss the theoretical and policy contributions of our work.

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A Micro-Level Data-Calibrated Agent-Based Model: The Synergy between Microsimulation and Agent-Based Modeling

Artificial Life ◽

10.1162/artl_a_00260 ◽

2018 ◽

Vol 24 (2) ◽

pp. 128-148

Author(s):

Karandeep Singh ◽

Chang-Won Ahn ◽

Euihyun Paik ◽

Jang Won Bae ◽

Chun-Hee Lee

Keyword(s):

Population Dynamics ◽

Census Data ◽

Social Issues ◽

Real Data ◽

Agent Based Modeling ◽

Population Census ◽

Agent Based ◽

Artificial Society ◽

Level Data ◽

The Future

Artificial life (ALife) examines systems related to natural life, its processes, and its evolution, using simulations with computer models, robotics, and biochemistry. In this article, we focus on the computer modeling, or “soft,” aspects of ALife and prepare a framework for scientists and modelers to be able to support such experiments. The framework is designed and built to be a parallel as well as distributed agent-based modeling environment, and does not require end users to have expertise in parallel or distributed computing. Furthermore, we use this framework to implement a hybrid model using microsimulation and agent-based modeling techniques to generate an artificial society. We leverage this artificial society to simulate and analyze population dynamics using Korean population census data. The agents in this model derive their decisional behaviors from real data (microsimulation feature) and interact among themselves (agent-based modeling feature) to proceed in the simulation. The behaviors, interactions, and social scenarios of the agents are varied to perform an analysis of population dynamics. We also estimate the future cost of pension policies based on the future population structure of the artificial society. The proposed framework and model demonstrates how ALife techniques can be used by researchers in relation to social issues and policies.

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Simulation of trends in the use of e-payment using agent based models

International Journal of Industrial Optimization ◽

10.12928/ijio.v1i1.1276 ◽

2020 ◽

Vol 1 (1) ◽

pp. 29

Author(s):

Elanjati Worldailmi ◽

Ismianti Ismianti

Keyword(s):

Economic Policy ◽

Central Bank ◽

Modeling And Simulation ◽

Theoretical Basis ◽

Agent Based Modeling ◽

Agent Based Models ◽

Economic Activities ◽

Agent Based ◽

Online Sales

Bank Indonesia (BI) as the central bank in Indonesia has launched a movement to use non-cash instruments in conducting transactions on economic activities. The majority of Indonesian people are increasingly ready to trade without cash or cashless society. The country's economic policy factors, the availability of various non-cash payments, and online sales and purchases, encourage the tendency to use non-cash transactions (e-payment). One way to find out these trends is to use a model. Models can help understand and explain real phenomena more easily and efficiently than directly observing. One model that can be used is Agent Based Modeling and Simulation (ABMS). By using ABMS, the development of models with complex behaviors, dependencies, and interactions can be developed more easily. ABMS is able to describe processes, phenomena, and situations. In this study, the factors that influence the tendency to use e-payment are obtained from various references. From these factors, then created a scenario as a sub-purpose of this model. In simulations using ABMS, detailed descriptions explained based on ODD Protocol elements can be more easily understood and complete. ODD systematically evaluates a model. The advantage is that ODD can improve the accuracy of model formulas and make the theoretical basis more visible.

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An Agent Based Modeling of COVID-19: Validation, Analysis, and Recommendations

10.1101/2020.07.05.20146977 ◽

2020 ◽

Cited By ~ 2

Author(s):

Md. Salman Shamil ◽

Farhanaz Farheen ◽

Nabil Ibtehaz ◽

Irtesam Mahmud Khan ◽

M. Sohel Rahman

Keyword(s):

New York ◽

New York City ◽

Emergency Service ◽

Service Providers ◽

Real Data ◽

Agent Based Modeling ◽

Contact Tracing ◽

Agent Based Model ◽

Agent Based ◽

The City

AbstractThe Coronavirus disease 2019 (COVID-19) has resulted in an ongoing pandemic worldwide. Countries have adopted Non-pharmaceutical Interventions (NPI) to slow down the spread. This study proposes an Agent Based Model that simulates the spread of COVID-19 among the inhabitants of a city. The Agent Based Model can be accommodated for any location by integrating parameters specific to the city. The simulation gives the number of daily confirmed cases. Considering each person as an agent susceptible to COVID-19, the model causes infected individuals to transmit the disease via various actions performed every hour. The model is validated by comparing the simulation to the real data of Ford county, Kansas, USA. Different interventions including contact tracing are applied on a scaled down version of New York city, USA and the parameters that lead to a controlled epidemic are determined. Our experiments suggest that contact tracing via smartphones with more than 60% of the population owning a smartphone combined with a city-wide lock-down results in the effective reproduction number (Rt) to fall below 1 within three weeks of intervention. In the case of 75% or more smartphone users, new infections are eliminated and the spread is contained within three months of intervention. Contact tracing accompanied with early lock-down can suppress the epidemic growth of COVID-19 completely with sufficient smartphone owners. In places where it is difficult to ensure a high percentage of smartphone ownership, tracing only emergency service providers during a lock-down can go a long way to contain the spread. No particular funding was available for this project.

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Simulation-based analyses of an evacuation from a metropolis during a bombardment

SIMULATION ◽

10.1177/0037549714551291 ◽

2014 ◽

Vol 90 (11) ◽

pp. 1244-1267 ◽

Cited By ~ 15

Author(s):

Jang Won Bae ◽

SeHoon Lee ◽

Jeong Hee Hong ◽

Il-Chul Moon

Keyword(s):

Initial Conditions ◽

Real Data ◽

Agent Based Modeling ◽

Agent Based Model ◽

Target Region ◽

Agent Based ◽

Virtual Experiments ◽

The Road ◽

Simulation Based ◽

The Military

The bombardment of a metropolis is considered a nightmare scenario. To reduce losses from such an assault, big cities have developed evacuation policies in case of bombardment. However, to build efficient evacuation policies, much footing data is required that considers both military and civilian views. Agent-based modeling and simulation could be utilized as a method to obtain the footing data. In this paper, we develop an evacuation agent-based model that describes a massive evacuation through the road network of a metropolis during a bombardment. In particular, our model took account of bombing strategies (i.e. the military view) as well as the characteristics of roads and evacuation agents (i.e. the civilian view) in order to analyze evacuations from both military and civilian perspectives. Moreover, we applied real data from a target region to calibrate parameters and initial conditions of the evacuation agent-based models, which increased the reliability of simulation results. Using the evacuation agent-based model, we designed and performed virtual experiments with varying military and civilian factors. Through the various analyses on the experiment results, we showed that our model could be a framework that provides footing data to develop efficient evacuation policies and preparations.

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