Variational Quantum Soft Actor-Critic

Understand

Quantum computing has a superior advantage in tackling specific problems, such as integer factorization and Simon's problem.

• For more general tasks in machine learning, by applying variational quantum circuits, more and more quantum algorithms have been proposed recently, especially in supervised learning and unsupervised learning.
• However, little work has been done in reinforcement learning, arguably more important and challenging.
• Previous work in quantum reinforcement learning mainly focuses on discrete control tasks where the action space is discrete.