Semantic Plan to Inform Digital Representation (SPIDR)

Army mission planning is complex and entails coordination across echelons in a dynamic environment. There is a significant opportunity to mitigate the complexity with new decision aiding systems. Chief among the challenges is designing a decision aiding system that appropriately represents the many planning artifacts, both digital and analog, as well as updating and integrating the dynamic entities and relationships needed for revising plans and courses of action in real-time. Future systems must satisfactorily represent the relationships between high level, abstract plans and low-level, detailed plans and provide system users an optimized view of the most relevant information for the task at hand while hiding at-the-moment irrelevant information. This requires comprehensive formal representations with defined semantics that spans the MDMP. Our approach will evaluate formalism to represent the mission planning concepts, algorithms to manipulate those concepts, and near-term aspects of the mission planning process. The ultimate goal of the system is to leverage a natural division of labor between human and machine to provide enough automation to improve the efficiency and effectiveness of mission planning while promoting a shared understanding of the planning so that human planners trust the system.