Machine Learning
Quantum computing helps reinforcement learning to take off
Reinforcement learning is often the most suitable AI solution for a range of applications in the sectors of autonomous systems, healthcare, and communication, due to the training method. Nevertheless, the nature of these tasks makes data collection potentially resource intensive or in some cases even unachievable. This is where reinforcement learning could benefit from embedding quantum computing methods since hybrid quantum-classical reinforcement learning was empirically shown to need less training steps to reach convergence. Fraunhofer IKS is researching solutions that are also suitable for use in industry.
Quantum computing