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 ...

Personalized learning systems aim to improve student engagement and outcomes by adapting to individual learning needs. Traditional models, however, struggle to handle the dynamic nature of student ...

To address the challenge of cooperative roundup of maneuvering targets under limited perception, this paper proposes TransMARL, a transformer-based multi-agent reinforcement learning framework for ...

Decision making in stochastic and dynamic environments plays an essential role in many areas, including finance, robotics, game theory, revenue management and social networks. This course aims to gain ...