Toward an AI-based external scenario event controller for crisis response simulations

There is a need for tool support for structured planning, execution and analysis of simulation-based training for crisis response and management. As a central component of an architecture for such tool support, we outline the design of an AI-based scenario event controller. The event controller is a component that uses machine reasoning to compute the next state in a scenario, given the actions performed in the corresponding simulation (execution of the scenario). Scenarios are specified in Answer Set Programming (ASP), which is a logic programming language we use for automated planning of training scenarios. A plan encoding in ASP adds expressivity in scenario specification and enables machine reasoning. For exercise managers this gives AI-based tool support for before-action and during-action reviews to optimize learning. In line with Modelling and Simulation as as Service, our approach externalizes event control from any particular simulation platform. The scenario, and its unfolding in terms of events, is externalized as a service. This increases interoperability and enables scenarios to be designed and modified readily and rapidly to adapt to new training requirements