Simulation of urban growth using agent-based modeling and game theory with different temporal resolutions

Kaviari, Farnaz; Mesgari, Mehran; Seidi, Ebrahim; Motieyan, Hamid

doi:10.1016/j.cities.2019.06.018

Cited by 35 publications

(16 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…With the rapid development of "3S" (GPS, remote sensing [RS], and GIS) technology and computer technology, geographical simulation has become a common way to analyze and predict geographical phenomena. Geographical models, such as cellular automata (CA) models and agent-based models, have been widely used and studied in the field of geographical simulation (Dahal & Chow, 2014;Kaviari, Saadi Mesgari, Seidi, & Motieyan, 2019;Li, Chen, Liu, Xu, & Chen, 2017;Wang et al, 2013;Xia, Wang, Zhang, & Zhang, 2018). The CA model, in particular, has been widely used to simulate urban growth because of its simple structure and convenient application (Xia, Zhang, Wang, Qiao, & Zhang, 2020).…”

Section: Introductionmentioning

confidence: 99%

Analyzing the effects of stochastic perturbation and fuzzy distance transformation on Wuhan urban growth simulation

Bin

Wang

et al. 2020

Transactions in GIS

View full text Add to dashboard Cite

Stochastic perturbation and fuzzy distance transformation (FDT) have been widely introduced into the derivation of transition rules to improve the simulation capability of urban cellular automata (CA) models. However, their effects on urban growth simulation have not been revealed. In this article, we compare their effects on urban growth simulation for the city of Wuhan by a sensitivity analysis of the simulation accuracy and simulated urban patterns. We reveal the relationship between the two components and propose an optimized stochastic variable to improve the simulation capability of urban CA models. The results show that the stochastic perturbation is the main factor affecting the simulation accuracy and simulated urban patterns of Wuhan, in that it significantly reduces the simulation accuracy and increases the degree of fragmentation and the proximity and shape complexity of the simulation results. In addition, the change caused by the stochastic perturbation increases with its intensity. Although FDT can restrain the effect of the stochastic perturbation, its inhibitory effect becomes negligible as the stochastic perturbation intensity increases. The optimized stochastic variable can significantly reduce the negative impact of the original stochastic variable, and its improvement is more obvious when the stochastic perturbation intensity is higher.

show abstract

Section: Introductionmentioning

confidence: 99%

Analyzing the effects of stochastic perturbation and fuzzy distance transformation on Wuhan urban growth simulation

Bin

Wang

et al. 2020

Transactions in GIS

View full text Add to dashboard Cite

show abstract

“…For example, the Increased population density scenario plays the primary role in protecting arable and ecological land at the regional scale. Nevertheless, in the Increase scenario, we enhance population density to reduce land consumption, although the exorbitant concentration of residents may result in various urban living and ecological problems [30,61]. When we consider the sub-regional scale, for those peri-urban and rural regions such as Pingshan, Yantian, and Dapeng, the sprawling urban form protects more arable land than other scenarios.…”

Section: Response Of Sub-regions To Alternative Scenariosmentioning

confidence: 99%

Trade-Off Relationship of Arable and Ecological Land in Urban Growth When Altering Urban Form: A Case Study of Shenzhen, China

et al. 2020

View full text Add to dashboard Cite

Over the last few decades, rapid urban expansion has spread over a great deal of arable and ecological land, leading to severe social and environmental issues. Although different urban growth scenarios cause varying types of urban forms to emerge, there is currently a lack of empirical studies and other research on these different forms. Therefore, it is important for decision-makers to have an improved understanding of the relationships between arable land and ecological land under different urban form conditions in order to implement sustainable urban development policies. This study utilized a patch-based, multilevel stochastic urban growth model to simulate Shenzhen’s urban growth until 2035. To determine the impacts of urban forms and population density on land use, we established five scenarios to simulate urban expansion and land-use changes at the sub-regional scale. The results revealed the trade-off relationships that emerge when altering the urban forms or population density, which shows that no single policy can conserve arable land and ecological land simultaneously. The results also revealed that sub-regions have distinct responses to alternative urban form scenarios compared with an entire region. Decision-makers and planners should consider the urban form in order to optimize development projects that fit local conditions and achieve more sustainable development.

show abstract

“…A zero-sum game, a non-cooperative game-theoretic model, was employed with ABM to model urban growth. 23 Yazan et al 24 adopted Stackelberg game-theoretical model, another type of non-cooperative game, with ABM for analyzing the strategic cooperative behavior in industrial symbiosis. De Andrade et al 25 used non-CGT with ABM to simulate spatial phenomena.…”

Section: Introductionmentioning

confidence: 99%

Computerized agents versus human agents in finding core coalition in glove games

2022

View full text Add to dashboard Cite

One of the challenges for agent-based modeling is being able to incorporate human behavior. Human behavior is a multifaceted phenomenon, with strategic coalition formation being one form. A hybrid agent-based modeling approach, called ABMSCORE, has been derived to emulate strategic group formation. In this paper, we describe a simulation experiment to compare the ABMSCORE with actual human behavior. The comparison criterion is the respective rates of finding an ideal coalition. In our experimental design, we go to great lengths to ensure the similarity of the scenarios in the two trial types: trials with computerized agents only and trials involving human participants when one of the computerized agents is replaced by an actual human. We did this to limit the number of possible extraneous variables introduced into the experimental system. The scenario considered is the glove game, a standard cooperative game that has been previously used in human experiments. Our results indicate that the ABMSCORE model produces similar rates of finding the ideal coalition as the human players; however, there are some limitations. This research provides evidence for using the ABMSCORE modeling approach to model human strategic coalition formation in agent-based models.

show abstract

Simulation of urban growth using agent-based modeling and game theory with different temporal resolutions

Cited by 35 publications

References 25 publications

Analyzing the effects of stochastic perturbation and fuzzy distance transformation on Wuhan urban growth simulation

Analyzing the effects of stochastic perturbation and fuzzy distance transformation on Wuhan urban growth simulation

Trade-Off Relationship of Arable and Ecological Land in Urban Growth When Altering Urban Form: A Case Study of Shenzhen, China

Computerized agents versus human agents in finding core coalition in glove games

Contact Info

Product

Resources

About