Adaptive Mission Planning: Evaluation of a Hybrid Cognitive Mixed-Initiative Planning Assistant in Manned-Unmanned Teaming Operations
Siegfried Maier, Jane Jean Kiam, Axel Schulte · 2024
This paper examines the integration of cognitive mixed-initiative assistance via a Planning Assistance Agent in the context of Manned-Unmanned Teaming operations. The aim is to enhance mission planning, replanning, and execution in complex military air operations. The agent employs a hybrid Mixed-Initiative-Planning approach to autonomously adjust and optimize mission plans in real time, with the objective of reducing pilot workload, increasing situational awareness, and maintaining high mission success rates without increasing the risk of losses of unmanned assets. The agent integrates current environmental data and tactical situation changes into its planning processes, thereby closing the so-called “cognitive loop”. This is made possible by the use of sophisticated algorithms and planning problem modeling languages. The effectiveness of the Agent was evaluated through the participation of German Air Force pilots in both static and dynamic mission simulations. The dynamic simulations were conducted in a fully integrated Manned-Unmanned-Teaming fighter simulator, while the static missions required the pilots to create mission plans on a separate workstation. The simulations assessed the impact of the Agent on mission success and the pilot performance under varying levels of assistance. The results demonstrated that a situation-adapted assistance, which allows for dynamic and autonomous tactical adjustments by the Agent, most effectively enhances operational performance and pilot engagement without overwhelming the pilot or causing the pilot to over rely on automated systems.