Findings in the Area of Flood Risk Management Reported from University of Tokyo (Modelling the Behaviour of Corporations During the Flood Damage Recovery Process Using Multi-agent Deep Reinforcement Learning): Risk Management – Flood Risk Management

Insurance Daily News

2022 OCT 06 (NewsRx) -- By a News Reporter-Staff News Editor at Insurance Daily News -- Research findings on Risk Management - Flood Risk Management are discussed in a new report. According to news originating from Tokyo, Japan, by NewsRx correspondents, research stated, “In the event of a flood, affected firms will experience production stoppages, resulting in supply chain (SC) disruptions and indirect economic damage to firms even outside the affected area. To mitigate the economic damage, it is essential for each firm in the entire SC to acquire a behavioural strategy in line with its recovery status.”

Financial support for this research came from Grants-in-Aid for Scientific Research (KAKENHI).

Our news journalists obtained a quote from the research from the University of Tokyo, “To achieve optimal behavioural strategies for individual firms in the recovery process, we present a learning framework using multi-agent simulation and deep reinforcement learning, which considers dynamically changing factors such as the flooding depth of buildings and roads, SC, labour and capital. The agents use reinforcement learning to make decisions about the dynamically changing environment and establish optimal action strategies during the recovery process. The model is trained using inundation simulation data from the Arakawa River located in Tokyo and inter-firm transaction data in Japan. The results show that the learned model can acquire behavioural strategies in the recovery process on a firm-by-firm basis, and to identify industries and regions with high economic damage.”

According to the news editors, the research concluded: “The results of this study can contribute to the development of recovery plans that consider the early recovery of SCs during floods.”

For more information on this research see: Modelling the Behaviour of Corporations During the Flood Damage Recovery Process Using Multi-agent Deep Reinforcement Learning. Journal of Flood Risk Management, 2022. Journal of Flood Risk Management can be contacted at: Wiley, 111 River St, Hoboken 07030-5774, NJ, USA. (Wiley-Blackwell - http://www.wiley.com/; Journal of Flood Risk Management - http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1753-318X)

The news correspondents report that additional information may be obtained from Shaofeng Yang, University of Tokyo, Graduate School of Frontier Sciences, Tokyo, Japan. Additional authors for this research include Yoshiki Ogawa, Koji Ikeuchi, Ryosuke Shibasaki and Yuuki Okuma.

The direct object identifier (DOI) for that additional information is: https://doi.org/10.1111/jfr3.12845. This DOI is a link to an online electronic document that is either free or for purchase, and can be your direct source for a journal article and its citation.