A simple implementation of using Q-Learning to find the shortest path between two nodes of a directed weighted graph.
The dw_graph.py file contains the code used to set up the environment and train our agent to solve the given task. The final q-table obtained after our agent has finished learning is stored in the Q_table.csv file. The shortest paths predicted by the agent on successfull execution of the program can be found in the shortest_paths.png file.