Scalable reinforcement learning (Glossary)

Scalable reinforcement learning is a term used in the fields of artificial intelligence, automation and Industry and Factory 4.0. Reinforcement learning is a method in which a computer programme learns to solve problems independently through trial and error and feedback. "Scalable" means that this learning method can be used not only for small tasks, but also for very large or complex applications.

Imagine, for example, a modern production line in a factory. In the beginning, an artificial intelligence (AI) may learn to optimally control just one machine. With scalable reinforcement learning, however, it is possible for the AI to control and improve more and more machines, processes and even the entire production chain independently over time - without having to learn from scratch every single time.

This makes scalable reinforcement learning particularly interesting for companies, as it helps to make processes more efficient, flexible and cost-effective - even if requirements or production sizes change. So if you are looking for future-proof and customisable automation or AI solutions, scalable reinforcement learning is a must.