In this assignment, you will apply the concepts you learned about in the previous few modules – neural networks, reinforcement learning, and Q-algorithms – to design the code for a pathfinding intelligent agent. Specifically, you will be designing code for a pirate non-player character (NPC) that is part of a larger treasure hunt video game. The pirate will need to navigate the game world, which consists of different pathways and obstacles, in order to find the treasure. The pirate agent’s goal is to find the treasure before the human player.
You have been provided with some starter code and a sample environment where your pirate agent will be placed. You will need to create a deep Q-learning algorithm to train your pirate agent. In this milestone, you will be turning in the code for your pirate intelligent agent so that you can receive feedback from your instructor before turning in your final code (along with your design defense) when submitting Project Two.
Your submission should be your completed Jupyter Notebook (IPYNB) file containing the code for your pirate intelligent agent. For this assignment, it is especially important to submit the work that you have completed, even if you were not able to complete the whole assignment. This will allow you to get feedback from your instructor before you submit the full Project Two, which is due in Module Seven.
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