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Dashley Rouwendal van Schijndel, Audun Stolpe, & Jo Erskine Hannay. (2021). Toward an AI-based external scenario event controller for crisis response simulations. In Anouck Adrot, Rob Grace, Kathleen Moore, & Christopher W. Zobel (Eds.), ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management (pp. 106–117). Blacksburg, VA (USA): Virginia Tech.
Abstract: There is a need for tool support for structured planning, execution and analysis of simulation-based training for crisisresponse and management. As a central component of an architecture for such tool support, we outline the design ofan AI-based scenario event controller. The event controller is a component that uses machine reasoning to computethe next state in a scenario, given the actions performed in the corresponding simulation (execution of the scenario).Scenarios are specified in Answer Set Programming, which is a logic programming language we use for automatedplanning of training scenarios. A plan encoding in ASP adds expressivity in scenario specification and enablesmachine reasoning. For exercise managers this gives AI-based tool support for before-action and during-actionreviews to optimize learning. In line with Modelling and Simulation as as Service, our approach externalizes eventcontrol from any particular simulation platform. The scenario, and its unfolding in terms of events, is externalizedas a service. This increases interoperability and enables scenarios to be designed and modified readily and rapidlyto adapt to new training requirements.
Jo Erskine Hannay, & Yelte Kikke. (2019). Structured crisis training with mixed reality simulations. In Z. Franco, J. J. González, & J. H. Canós (Eds.), Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management. Valencia, Spain: Iscram.
Abstract: We argue that current technology for crisis training does not explicitly cater well enough for managing training
objectives and skill building metrics throughout the lifespan of training. We suggest how successful crisis training
may be enabled by interoperating next-generation exercise management tools with mixed-reality simulations. We
propose an architecture consisting of (1) a front-end in which training objectives, essential skills, corresponding
events and metrics can be declared, (2) a back-end consisting of simulations that implement the events and metrics
and (3) a middleware which transfers information between the front-end and back-end to enable semi-automatic
composition of the simulations and performance analysis. The purpose of this architecture is to facilitate learning
through the principles of deliberate practice. We indicate where emerging technologies are necessary to achieve this.