Live Quantum Circuits Visualizator for Reinforcement Learning

This project implements variational quantum circuits as action-value functions in deep Q-learning applied to a stochastic 4x3 grid world. It features a GUI for live visualization of circuit parameters, policies, rewards, and training metrics. It supports command-line training and provides reproducibility with original implementations and bug-fixes from an academic internship project at Porto University in 2024.