The main aim of the present work is to establish connections between the theory of dynamic programming and the statistical decision theory. The paper deals with a nonMarkovian dynamic programming ...

This paper proposes a distributed solution approach to a certain class of dynamic resource allocation problems and develops a dynamic programming-based multiagent decision-making, learning, and ...

Sequential decision-making under uncertainty is a foundational topic in multiple fields - including economics, operations research, and computer science, built around the foundation of Markov decision ...

Conventional Artificial Intelligence (AI) systems, particularly Large Language Models (LLMs) and Large Multimodal Models (LMMs), primarily rely on language, pre-trained historical data, and mimicking ...