2017
IJCAI
IJCAI 2017
Emergency Evacuation Simulator (EES) - a Tool for Planning Community Evacuations in Australia
Abstract
This work addresses the problem of encoding cognitive agents that are capable of complex reasoning beyond simple rules, within agent-based models (ABM). This is particularly important for social simulation where agents represent people. We provide a general solution to this problem through infrastructure that allows the integration of state-of-the-art Belief-Desire-Intention (BDI) and ABM systems. In this paper, we demonstrate how this infrastructure is being used to help emergency services in Australia plan for community evacuations.
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Keyword Pioneer
— agent-based modeling
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Cross-Pollinator
— Artificial Intelligence, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning