Policy Gradients using Variational Quantum Circuits

Understand

Variational Quantum Circuits are being used as versatile Quantum Machine Learning models.

• Some empirical results exhibit an advantage in supervised and generative learning tasks.
• However, when applied to Reinforcement Learning, less is known.
• In this work, we considered a Variational Quantum Circuit composed of a low-depth hardware-efficient ansatz as the parameterized policy of a Reinforcement Learning agent.