AI InnovationsMIT News
Researcher uses reinforcement learning to fix complex systems
Can artificial intelligence help untangle problems as messy as traffic? According to MIT News, Associate Professor Cathy Wu uses reinforcement learning, a type of machine learning where a system learns by trial and error, to map out improvements to transportation and other complicated systems. Her work treats these systems as networks with many moving parts that affect each other. By modeling how small changes ripple through a system, the approach could help planners find better ways to manage multifaceted challenges, from easing congestion to improving other large-scale infrastructure.
Words to know
- Reinforcement learning
- — A machine learning method where a system improves by trying actions and learning from outcomes.
- Multifaceted systems
- — Complex systems with many interacting parts, like transportation networks.
Summary written from MIT News's headline and teaser