Thesis Description & Objectives
The thesis work will focus on the development of a hybrid quantum-classical reinforcement learning agent and its subsequent application to optimize energy consumption within a simulated data-center environment. The student will work with well-established frameworks for classical reinforcement learning and machine learning, such as Gymnasium and PyTorch, as well as with frameworks for quantum programming, including Qiskit and PennyLane.
