Deep Learning for Sequential Decision Making under Uncertainty: Foundations, Frameworks, and Frontiers

arXiv:2604.11507v1 Announce Type: cross Abstract: Artificial intelligence (AI) is moving increasingly beyond prediction to support decisions in complex, uncertain, and dynamic environments. This shift creates a natural intersection with operations research and management sciences (OR/MS), which have long offered conceptual and methodological foundations for sequential decision-making under uncertainty. At the same time, recent advances in deep learning, including feedforward neural networks, LST