Qubits for industrial applications

The QLindA project combines quantum computing with Al processes for industrial applications

© iStock, Fraunhofer IIS
Using quanta to realize reinforcement learning for industrial applications

Quantum physics is finding its way into technology developments that aim to make industrial applications more efficient using artificial intelligence (Al) and machine learning. In the QLindA project, we are researching how to combine quantum computing with Al technologies for what is known as reinforcement learning (RL). Our project partners are Friedrich-Alexander-Universität Erlangen-Nürnberg, OTH Regensburg and the companies Siemens and IQM. In this process, a system goes through trial-and-error cycles to independently learn the best strategy for achieving the goal. Together with users, the scientists are investigating how RL can be realized on quantum computers. Potential applications include optimizing control based on reinforcement learning in process manufacturing, implementing distributed automation systems in the smart factory, and optimizing production planning. The project got underway last year with funding from the German Federal Ministry of Education and Research. The content is the development of novel algorithms for operating quantum computers, the evaluation of methods, the creation of a library for use in industrial applications, as well as considerations of the potential and limitations of using the algorithms.

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