Study the gridworld_value_iteration.ipynb notebook that trains an agent to navigate a simple Grid World using Value Iteration. Make a GIF containing the following agents
- (10 marks) Random
- (30 marks) Monte Carlo
- (30 marks) Q-Learning
- (30 marks) SARSA
solving a 5x5 GridWorld with 5 holes. There should be 2 holes close to the starting position, 2 holes close to the goal, and 1 hole somewhere else. Ensure that the grid is solvable, yet challenging.
Submit your code and your GIF in the Google Classroom.