Cognitive Modeling for Effective Emergency Response: An Agent-Based Simulation Architecture

In the time of crisis, however, it would be of particular importance to have a swift and competent emergency response in order to minimize the risks and casualties. While the old-fashioned way of emergency planning and exposition of protocols might fail in the midst of the fast changing and complex events. The present article introduces a new technique on how to step up emergency response through cognitive modeling and agent-based simulation architecture. Taking account of cognitive science as well as theory of artificial intelligence we do use cognitive model to mimic man-like making of critical decisions in emergency events. The nature of the proposed architecture is that it includes side agents, e.g.first responders, authorities, and population, which have humanized intelligent functioning. Simulation architecture can be divided into the following elements: the environment modeling, the agent behavior modeling, and the decision-making algorithms. Environment can be modeled that takes account of spatial and temporal aspects of the crisis situation and agent behavior modeling captures its cognitive elements in forming decision, communication and coordination. These algorithms allow the agents to make decisions on the fly using multicriteria analysis, assessing the situation, and performing actions in real-time. By extensive usage of simulations and validation studies, suggested method to be efficient and our approach shows the increased improvement in the emergency response operations. The simulation platform that is based on our architecture helps stakeholders to explore various options, predict the consequences and identify any potential bottlenecks thereby gives power to the decision makers to take informed decisions and efficient resource allocation. In general, our study enriches the thinking around cognitive modeling frameworks for emergency management and introduces a potent tool for capacity building, planning, and monitoring the emergency response strategies. We hope that our agent-based simulation model will become popular, allowing decision makers to build up readiness and a more sustainable post-crisis world.