mccormick.northwestern.edu

IEMS 469: Dynamic Programming

This course covers reinforcement learning aka dynamic programming, which is a modeling principle capturing dynamic environments and stochastic nature of events. The main goal is to learn dynamic ...
Nature

Integrating Reinforcement Learning with Dynamic Knowledge Tracing for personalized learning path optimization

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 ...
mccormick.northwestern.edu

IEMS 408: Decision Making in Dynamic Learning Environments

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 ...
Nature

RRT-guided experience generation for reinforcement learning in autonomous lane keeping

Reinforcement Learning has emerged as a significant component of Machine Learning in the domain of highly automated driving, facilitating various tasks ranging from high-level navigation to control ...