In this project, we are going to implement dynamic programming to search the shortest path for the Door-Key problems. The objective of the agent is to get from start to goal with the least amount of the moves.

There are 7 test scenes you have to test and include in the report.

doorkey-5x5-normal

doorkey-6x6-normal	doorkey-6x6-direct	doorkey-6x6-shortcut

doorkey-8x8-normal	doorkey-8x8-direct	doorkey-8x8-shortcut

• Install gym-minigrid
• Install dependencies

pip install -r requirements.txt

doorkey.py the main entrance of the program.

You might find some useful tools in utils.py

• step(): Move your agent
• generate_random_env(): Generate a random environment for debugging
• load_env(): Load the test environments
• save_env(): Save the environment for reproducing results
• plot_env(): For a quick visualization of your current env, including: agent, key, door, and the goal
• draw_gif_from_seq(): Draw and save a gif image from a given action sequence.

• get_next_state(): Motion model x_t+1 = f(x, u)
• step_cost(): the cost of action
• terminal_cost(): cost when reaching the goal
• DP(): main dynamic programming, computing optimal policy