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

Qing Yang,Xu Sun,Xingxing Liu,Jinmei Wang

doi:10.3390/w12041190

Abstract

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.

Highlights

Urban rainstorms are a type of major natural disaster and induce enormous loss [1]
Based on D-recognition-primed decision (RPD) theory, we model agents that can update their strategies based on their experience gained in the process of the rainstorm
Individuals often make decisions based on previous experience

Summary

Introduction

Urban rainstorms are a type of major natural disaster and induce enormous loss [1]. The urban rainstorms may cause a seeper phenomenon noted as waterlogging too [2], which frequently happens in many big cities around the world, especially in the developing countries [3]. The 7/21 accident occurred in Beijing, China, on 21 July 2012, caused 79 deaths, and a great direct economic loss of. 11.64 billion RMB [4]. In addition to direct damage, some indirect loss caused by the rainstorm is huge. Waterlogging and low visibility in the urban rainstorms will give rise to traffic problems and other derivative accidents [5]. It is critical to study how to reduce the loss caused by urban rainstorms

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Conclusion