Proposal of a rescue simulator using an agent mechanism with expert disaster response strategy

Abstract

Japan has experienced many disasters in the past, but there is a gap in the ability to respond to disasters depending on the region. Therefore, it is hoped that the use of agent simulators for disaster response will provide virtual experience in response. However, there are still many regions that do not know the correct strategies due to lack of experience and are unable to effectively use the agent-based strategy planning system. Therefore, we attempt to bridge the gap in response capability between regions by transferring strategies from regions with rich experience in disaster response to other regions with insufficient experience. Specifically, we will construct a disaster response simulator with expert agent functions that simulates the rescue strategies of experienced agents and utilizes the expert strategies imitated by the agents in the process when the simulator is used in other regions to support strategy planning. However, it is inconvenient if the strategies of the agents are uniform, because the quality of their activities is evaluated differently in each region, such as whether or not they have experienced a disaster. In order to solve this problem, we add a mechanism that can be modified by the decision makers who use the system, and introduce a framework of HITL that continuously learns from people for better strategies.