Applying The Soar Architecture To Model Cognitive Functions In A Kill Chain
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Accurate, relevant and timely combat identification (CID) enables the warfighter to locate and identify critical airborne targets with high precision. The current CID processes include the use of Naval and Joint combinations of platforms, sensors, networks and decision makers. There are diversified doctrines, rules of engagements, knowledge repositories and expert systems used in the current process to address the complexity of decision making challenges. However, the process is still very manual and decision makers can experience cognitive overload. Soar is a software and architecture system that models complex reasoning, cognitive functions and decision making. It can be used to model cognitive decisions for tactical warfare such as engagement decisions in a kill chain. The cognitive functions include decision making, sensor fusion, analytic processes and workflow. We used Soar to aid in the in the CID decision making process. We used Soar and specifically the reinforcement learning (RL) method for the cognitive functions of the CID decision making process. For this focus, the problem space has been characterized. Soar production rule pseudocodes, and the procedural knowledge and basis for reasoning were formulated in the project. We also produced a use case, a prototype and a student thesis.
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