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 ...

Because artificial intelligence is always learning, its introduction in government means agencies must continually adapt as well, as must leaders who want to evolve their management styles.

In this paper, we consider a finite-horizon stochastic mixed-integer program involving dynamic decisions under a constraint on the overall performance or reliability of the system. We formulate this ...

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 ...

In today’s fast-evolving property management landscape, success depends on strategic, well-informed decisions. Rising competition, heightened tenant expectations and operational complexities have ...

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 ...

This paper presents an experiment that is designed to be more effective than previous studies at reproducing in the laboratory the affective experiences of risk-taking, such as hope, fear, thrill, ...

FORT KNOX, KY – Leaders from the 244th Expeditionary Combat Aviation Brigade gathered around the table, plotted their air corridors, and collaborated in the preparation for their aerial assault ...

In the dynamic world of corporate reporting and planning, the terminology we use often reflects deeper shifts in strategy and technology. Over the years, we’ve witnessed the rise and fall of buzzwords ...

Data stands out as a key resource for retailers in the increasingly digital world. Businesses are generating more data than ever before, from transaction records and customer profiles to social media ...