QuantumRepeaterChainPolicyRL

A reinforcement learning (RL) framework written in C++ as a building block for quantum network control. The code implements the MDPs from the work titled "Reinforcement Learning for Quantum Network Control with Application-Driven Objectives," using policy gradients and the chain rule to optimize arbitrary non-linear objectives, specifically in a quantum setting where the inputs to these objectives may not be scalars.

Hyperparameters used to generate the CSVs are recorded in config/config.yaml.