Towards Neuro-Symbolic Reinforcement Learning For Trustworthy Human-Autonomy Teaming

Artificial Intelligence (AI) has shown a tremendous impact on civilian and military applications. However, traditional AI will remain inadequate because of issues such as explicit and implicit biases and explainability for operating independently in dynamic and complex environments for the foreseeable future. For human-autonomy teaming (HAT), trustworthy AI is crucial since machines/autonomy and humans work in collaboration for shared learning and joint reasoning for a given mission with combat speed and high accuracy, trust, and assurance. In this paper, we present a brief survey of recent advances, some key challenges, and future research directions for neuro-symbolic-reinforcement-learning-enabled trustworthy HAT.