Keywords
finance
uav
Abstract
This review examines curriculum-guided risk reasoning across autonomous and financial decisions through an evidence-centered design lens. The analysis asks how uncertainty should alter ranking, escalation, and landing verification. It treats the relevant unit as a complete pathway from data or physical observations to representation, model output, human interpretation, and accountable action. The cited literature is synthesized without inventing experiments or unreported performance values. Particular attention is given to a transferable model hiding domain-specific failure costs. The review argues that credible translation requires explicit evidence boundaries, uncertainty-aware evaluation, author-visible traceability, and a documented route for intervention. The resulting framework supports high-stakes screening and autonomous operation while distinguishing component promise from system readiness.
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