Reinforcement Learning

Category: science

An ML branch where an agent learns to make decisions by performing actions and receiving rewards or penalties.

This is the "training by trial." Think of a video game AI. It tries 1,000 ways to win, gets a "point" for good moves, and a "minus" for bad ones. It’s ideal for high-speed automated trading or robotics where you need the model to learn through real-time feedback loops.

Common Examples

• We are experimenting with reinforcement learning for our automated order-routing engine, letting it "learn" the most liquid trading venues.
• Reinforcement learning is unique because it doesn’t require labeled datasets; it learns through the experience of its own interactive decisions.