Collection planning for multi-domain operations is a complex task that requires knowledge of mission objectives, intelligence needs and gaps, and collection asset schedules, availability, and capabilities. Currently, collection planners rely on Microsoft Office tools to document their plans and have very little interaction with the plans of collection managers in other units and across the enterprise, resulting in redundancies and inefficiencies. In response to this problem, Aptima, Inc. and our partner Patch Plus Consulting, Inc. propose Collection Optimization and Generation Synchronized with Optempo Reasoning Tailored to Humans (COGSWORTH). COGSWORTH will be an adaptive cognitive assistant that will implement a data structure to enable artificial intelligence (AI) to reason over collection plans, assets availability, and mission objectives to generate optimal collection plans. The innovation of COGSWORTH is in its learning of user preferences to improve its own performance in planning and mission performance that results from its optimization of planning across units and asset levels. The HEFT (Heterogeneous Earliest Finish Time) algorithm will be used to create plans that account for tasking, timing, and platform constraints. The HEFT algorithm assigns weight to tasks and tasks to platforms to generate plans. Collection plans will be presented to users in an intuitive, friendly interface for selection, ranking, and feedback. Machine learning (ML) will integrate the feedback from the user into the algorithms weighting of tasks, resulting in a system that learns and improves over time. COGSWORTH will reduce the redundancy of collection plans, enable cooperation and coordination, and enhance the coverage of mission objectives to improve the efficiency of collection plans. Phase I will produce a proof of concept of the custom data format, user interface, and underlying AI/ML prototype algorithms. The option period will result in an enhanced prototype with a collaboration platform and evaluation report, setting the stage for rapid development in Phase II and beyond.
