Advances in machine learning applications for scenario intelligence: deep learning

摘要

In this paper, we discuss the inextricable link between automatingrntraining environment adaptation and deep understanding of therncontext surrounding specific decisions and actions executed in thernperformance environment. To enable deep contextual understanding,rnpsychological measurement strategies are needed to more accuratelyrnand rapidly model the psychologically meaningful details of therntrainee’s interactions with events, objects, and people in the trainingrnenvironment. As these interactions often entail complex, nonlinearrncue-action relationships, the underlying models must effectivelyrncapture the nuance, complexity, and largely intuitive nature ofrnhuman decision-making. This paper discusses the promise of anrnemerging field of machine learning u0001 deep neural networks u0001 forrnsupporting this requirement.