Gerhard Wickler, Austin Tate, & Stephen Potter. (2007). Integrating discrete event and process-level simulation for flexible training in the I-X framework. In K. Nieuwenhuis P. B. B. Van de Walle (Ed.), Intelligent Human Computer Systems for Crisis Response and Management, ISCRAM 2007 Academic Proceedings Papers (pp. 355–359). Delft: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: The aim of this paper is to describe I-Sim, a simulation tool that is a fully integrated part of the underlying agent framework, I-X. I-Sim controls a discrete event simulator, based on the same activity model that is shared between all I-X components, and multiple process-level simulators that model the continuous change caused by actions that are considered as primitives by the rest of the system. The primary purpose of this tool is to support instructors during exercises that are used for training in emergency response. The main advantage the I-Sim tool gives the instructors is flexibility, allowing them to orchestrate and modify existing training scenarios on the fly, adapting them to trainees' needs as required.
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Tomoichi Takahashi. (2007). Agent-based disaster simulation evaluation and its probability model interpretation. In K. Nieuwenhuis P. B. B. Van de Walle (Ed.), Intelligent Human Computer Systems for Crisis Response and Management, ISCRAM 2007 Academic Proceedings Papers (pp. 369–376). Delft: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: Agent-based simulations enable the simulation of social phenomenon by representing human behaviors using agents. Human actions such as evacuating to safe havens or extinguishing fires in disaster areas are important during earthquakes. The inclusion of human actions in calculating the damage at disaster sites provides useful data to local governments for planning purposes. In order to practically apply these simulation results, these results should be tested using actual data. Further, these results should be analyzed and explained in a manner that people who are not agent programmers can also understand easily. First, the possibility of applying agent-based approaches to social tasks is shown by comparing the simulation results with those obtained from other methods. Next, we propose a method to present agent behaviors using a probability model and discuss the results of applying this method to the RoboCup Rescue simulation data. These will delve into future research topics for developing agent based social simulations to practical ones.
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Alexander Smirnov, Mikhail Pashkin, Nikolay Shilov, & Tatiana Levashova. (2007). Intelligent support of context-based megadisaster management: Hybrid technology and case study. In K. Nieuwenhuis P. B. B. Van de Walle (Ed.), Intelligent Human Computer Systems for Crisis Response and Management, ISCRAM 2007 Academic Proceedings Papers (pp. 305–316). Delft: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: The situation with the hurricane Katrina showed that the conventional tiered response to disaster event, whereby state and local officials are responsible for the first few days, does not work well in case of megadisasters (massive hurricanes, earthquakes, large-scale acts of terrorism, etc.). Such situations require application of new technologies for preparing the operation, interoperability between the operation participants, and decision support for officials. Here presented approach proposes a context-driven decision support schema based on integration of such technologies as context & ontology management and constraint satisfaction. The application of the approach is illustrated via a case study of a portable hospital arrangement.
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Stephen Potter, Yannis Kalfoglou, Harith Alani, Michelle Bachler, Simon Buckingham Shum, Rodrigo Carvalho, et al. (2007). The application of advanced knowledge technologies for emergency response. In K. Nieuwenhuis P. B. B. Van de Walle (Ed.), Intelligent Human Computer Systems for Crisis Response and Management, ISCRAM 2007 Academic Proceedings Papers (pp. 361–368). Delft: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: Making sense of the current state of an emergency and of the response to it is vital if appropriate decisions are to be made. This task involves the acquisition, interpretation and management of information. In this paper we present an integrated system that applies recent ideas and technologies from the fields of Artificial Intelligence and semantic web research to support sense-and decision-making at the tactical response level, and demonstrate it with reference to a hypothetical large-scale emergency scenario. We offer no end-user evaluation of this system; rather, we intend that it should serve as a visionary demonstration of the potential of these technologies for emergency response.
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Philippe Kruchten, Carson Woo, Kafui Monu, & Mandana Sotoodeh. (2007). A human-centered conceptual model of disasters affecting critical infrastructures. In K. Nieuwenhuis P. B. B. Van de Walle (Ed.), Intelligent Human Computer Systems for Crisis Response and Management, ISCRAM 2007 Academic Proceedings Papers (pp. 327–344). Delft: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: Understanding the interdependencies of critical infrastructures (power, transport, communication, etc.) is essential in emergency preparedness and response in the face of disasters. Unfortunately, many factors (e.g., unwillingness to disclose or share critical data) prohibited the complete development of such an understanding. As an alternative solution, this paper presents a conceptual model-an ontology-of disasters affecting critical infrastructures. We bring humans into the loop and distinguish between the physical and social interdependencies between infrastructures, where the social layer deals with communication and coordination among representatives (either humans or intelligent agents) from the various critical infrastructures. We validated our conceptual model with people from several different critical infrastructures responsible for disasters management. We expect that this conceptual model can later be used by them as a common language to communicate, analyze, and simulate their interdependencies without having to disclose all critical and confidential data. We also derived tools from it.
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