An agent-based simulation system for evaluating gridding urban management strategies

Gao, Lei; Durnota, Bohdan; Ding, Yongsheng; Dai, Hua

doi:10.1016/j.knosys.2011.07.018

Cited by 17 publications

(3 citation statements)

References 37 publications

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“…After passing one waterlogging point, they will lose some energy and time, but gain some experience as to where to wade directly or cautiously. Expert knowledge (EK) and participant observation (PO) can be used to understand agents and their actions [11]. Detailed agent attribute data is from Hubei Meteorological Service, Civil Affairs Bureau of Wuhan, data analysis of rainstorms in Wuhan [32], and study of the mitigation behavior in floods [33].…”

Section: Framework Of Multi-agent Simulationmentioning

confidence: 99%

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Multi-Agent Simulation of Individuals’ Escape in the Urban Rainstorm Context Based on Dynamic Recognition-Primed Decision Model

Qing

Sun

Liu

et al. 2020

Water

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The urban rainstorm can evolve into a serious emergency, generally characterized by high complexity, uncertainty, and time pressure. It is often difficult for individuals to find the optimal response strategy due to limited information and time constraints. Therefore, the classical decision-making method based on the “infinite rationality” assumption is sometimes challenging to reflect the reality. Based on the recognition-primed decision (RPD) model, a dynamic RPD (D-RPD) model is proposed in this paper. The D-RPD model assumes that decision-makers can gain experience in the escaping process, and the risk perception of rainstorm disasters can be regarded as a Markov process. The experience of recent attempts would contribute more in decision-making. We design the agent according to the D-RPD model, and employ a multi-agent system (MAS) to simulate individuals’ decisions in the context of a rainstorm. Our results show that experience helps individuals to perform better when they escape in the rainstorm. Recency acts as a one of the key elements in escaping decision making. We also find that filling the information gap between individuals and real-time disaster would help individuals to perform well, especially when individuals tend to avoid extreme decisions.

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Section: Framework Of Multi-agent Simulationmentioning

confidence: 99%

“…The rainstorm disaster is a typical complex society system [10]. Given the complexity of human activities, agent-based modelling and simulation (ABMS) shows great advantages in urban emergencies [11]. Through ABMS, the disaster Considering great similarities among regional plans in Wuhan, we have selected a typical community in this study.…”

Section: Introductionmentioning

confidence: 99%

Multi-Agent Simulation of Individuals’ Escape in the Urban Rainstorm Context Based on Dynamic Recognition-Primed Decision Model

Qing

Sun

Liu

et al. 2020

Water

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“…Wang et al summarized the model of GUM through integration of the modern urban management theory and "digital city" technology [1,2,3,4,5]. Kong et al discussed the various aspects of urban grid management system constitutes and framework [6], Gao et al established an agent-based simulation system for evaluating gridding urban management strategies [7].…”

Section: Introductionmentioning

confidence: 99%

Discussion of the Integrated Giddied Urban Management

Wang

Chen

2013

AMM

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This paper concentrates on the gridding urban management (GUM). In the background of the rapid development of the process of urbanization and urban-scale, based on computer grid technology and space grid technology, Integrated Gridding Urban Management (IGUM) of the modern city is established, which included city management, economic management and social management into the areas of urban grid system. This model manages to further enrich the contents of the urban grid management. Furthermore, Knowledge-based gridding urban management (KGUM) mode is put up for the future of the smart-sensor city to realize real-time dynamic and intelligent city management.

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