A framework with reasoning capabilities for crisis response decision-support systems

This paper reviews the methods in decision-support systems for crisis management. While much research has been conducted in this field, little emphasis has been placed on the uncertainty representation, reasoning, learning and real time decision-making capabilities of system. The purpose of this paper is to explore the basic assumptions of constructing an intelligent decision-support system for crisis response management. A novel framework for crisis response decision-making system under the assumption of openness to various kinds of uncertainties, reasoning and learning with real-time response is proposed. We applied the Non-Axiomatic Logic in representing and reasoning the uncertainty knowledge in the framework and demonstrated the reasoning and learning mechanisms of the framework through an application in a case study in the field of urban firefighting. The results show that the framework provides a suitable model for intelligent crisis response decision support systems.