Abstract
Goal-driven autonomy (GDA) is a reflective model of goal reasoning combining deliberative planning and plan execution monitoring. GDA’s is the focus of increasing interest due in part to the need to ensure that autonomous agents behave as intended. However, to perform well, comprehensive GDA agents require substantial domain knowledge. In this paper I focus on our work to automatically learn knowledge used by GDA agents. I also discuss future research directions.
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