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 ...

The field of dynamic decision making encompasses the study of how individuals and groups process, learn, and adapt their decision strategies within fluctuating and temporally evolving environments. In ...

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 ...