Study the gridworld_value_iteration.ipynb notebook that trains an agent to navigate a simple Grid World using Value Iteration, and perform the following modifications.
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(40 marks) Make a new notebook called GridWorld_3H.ipynb. Train an agent for a GridWorld with 3 holes. Visualize V, the policy, and the Q-table. Save GIF of the agent in action.
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(60 marks) Make a new notebook called GridWorld_RandomStart.ipynb. Train an agent that starts at a random location. Visualize V, the policy, and the Q-table. Save GIF of the agent in action.
Submit notebooks and your visualizations in the Google Classroom.