Quantum-assisted reinforcement learning is a term used in the fields of artificial intelligence, automation, industry and Factory 4.0. It is a new method for machines and computers to learn faster and smarter by utilising the special capabilities of quantum computers.
Reinforcement learning is a type of machine learning in which an artificial intelligence learns to become smarter through trial and error - similar to how children or animals learn from their experiences. In the quantum-assisted approach, certain computing processes are carried out on quantum computers. These computers can run through many possibilities at the same time, thereby significantly accelerating the learning processes.
Imagine that a robot in a factory has to learn how to assemble components more efficiently. With conventional technology, learning takes many days because each possibility has to be tested individually. With quantum-assisted reinforcement learning, the robot can try out many combinations simultaneously and learns in hours what would otherwise take days. This leads to faster improvements, higher productivity and lower costs.
Quantum-assisted reinforcement learning offers great potential to further optimise processes, especially for companies that rely on automation.
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