An embodied and cognitive model of figther pilot high level air-to-air engagement decision

Abstract

The development of pilot models has been a long-standing interest in cognitive modeling and AI due to the potential gains they offer in aerial robotics. In this study, a cognitive and embodied fighter pilot model is developed to obtain pilot-like characteristics for making high-level decisions in air-to-air engagements, using spiking neurons in ensembles implemented in the Neural Engineering Objects (NENGO) framework (Bekolay et al., 2014; Eliasmith, 2015). One major problem that is faced when creating such complex decision models is factoring the effect of the human agent’s affective state into the model, where emotional aggression may lead to irrational decisions. To address this need, inputs representing affective states that can influence the other subnetworks were included in the model. The NENGO framework also allowed for the use of Semantic Pointers, which allowed the numerical outputs of the spiking neuron ensembles to be expressed verbally as a semantic output. The inputs, final outputs (decisions), and intermediary decisions of the model were then evaluated by real-life warfighter pilots to assess the accuracy and validity of the model.