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 ...
VentureBeat

Stanford AI researchers introduce LILAC, reinforcement learning for dynamic environments

Want smarter insights in your inbox? Sign up for our weekly newsletters to get only what matters to enterprise AI, data, and security leaders. Subscribe Now Researchers from Stanford AI Lab (SAIL) ...
Forbes

The Autonomous Advantage: Reinforcement Learning’s Role In The Next Era Of AI

The age of truly autonomous artificial intelligence, where systems proactively learn, adapt and optimize amid real-world complexities instead of simply reacting, has been a long-held aspiration. Now, ...
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 ...
Forbes

From Turing To DeepSeek, Reinforcement Learning Soars To AI Summit

Using a bunch of carrots to train a pony and rider. (Photo by: Education Images/Universal Images Group via Getty Images) Andrew Barto and Richard Sutton are the recipients of the Turing Award for ...