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 ...
Nature

Dynamic-layer transformer-based reinforcement learning for observation-constrained multi-agent roundup scenarios

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 ...
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 ...
mccormick.northwestern.edu

IEMS 490: Optimization and Learning in Stochastic Dynamic Environments

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 ...
The Conversation

What is reinforcement learning? An AI researcher explains a key method of teaching machines – and how it relates to training your dog

Understanding intelligence and creating intelligent machines are grand scientific challenges of our times. The ability to learn from experience is a cornerstone of intelligence for machines and living ...