Reinforcement Learning with Quantum Variational Circuits

Understand

The development of quantum computational techniques has advanced greatly in recent years, parallel to the advancements in techniques for deep reinforcement learning.

• This work explores the potential for quantum computing to facilitate reinforcement learning problems.
• Quantum computing approaches offer important potential improvements in time and space complexity over traditional algorithms because of its ability to exploit the quantum phenomena of superposition and entanglement.
• Specifically, we investigate the use of quantum variational circuits, a form of quantum machine learning.