Competencies In this project, you will demonstrate your mastery of the following competencies: Explain the basic concepts and techniques that pertain to artificial intelligence and intelligent systems Analyze how algorithms are used in artificial intelligence to solve a variety of complex problems Scenario You are working as an AI developer for a gaming company. The company  is developing a treasure hunt game where the player needs to find the  treasure before the pirates find it. As an AI developer, you have been  asked to design an intelligent agent of the game for an NPC (non-player  character) to represent the pirate. 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. This is commonly called a pathfinding problem, as the agent you create will need to find a path towards its goal. 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. Finally,  you have also been asked to write a design defense that demonstrates  your understanding of the fundamental AI concepts involved in creating  and training your intelligent agent. Directions Pirate Intelligent Agent As part of your project,  you will create a pirate intelligent agent to meet the specifications  that you have been given. Be sure to review any feedback that you  received on your Project Two Milestone before submitting the final  version of your intelligent agent. Follow these steps to complete your  intelligent agent: Before creating your pirate intelligent agent, be sure to review the  Pirate Intelligent Agent Specifications document, located in the  Supporting Materials section. This document provides details about the  code that you have been given, and what aspects you will need to create. Download the zipped folder containing your starter code and Jupyter  Notebook files by using the link in the Supporting Materials section.  Access the Virtual Lab (Apporto) by using the link in the Virtual Lab Access  module. Upload the zipped folder into the Virtual Lab, unzip the  folder, and upload the files into the Jupyter Notebook application. Use  the tutorials in the Supporting Materials to help you with these tasks. Be sure to review the starter code that you have been given. Watch  the Project Two Walkthrough video, located in the Supporting Materials  section, to help you understand this code in more detail. IMPORTANT: Do not modify any of the PY files that you have been given. Complete the code for the Q-Training Algorithm section in your Jupyter Notebook. In order to successfully complete the code, you must do the following:  Develop code that meets the given specifications:  Complete the program for the intelligent agent so that it achieves its goal: The pirate should get the treasure. Apply a deep Q-learning algorithm to solve a pathfinding problem. Create functional code that runs without error. Use industry standard best practices such as in-line comments to enhance readability and maintainability. After you have finished creating the code for your notebook, save  your work. Make sure that your notebook contains your name in the  filename (such as, “Doe_Jane_ProjectTwo.ipynb”). This will help your  instructor access and grade your work easily. Be sure to download a copy  of your notebook (IPYNB file) for your submission. Design Defense As a part of your project, you  will also submit a design defense. This design defense will demonstrate  the approach you took in solving this problem, explain how the  intelligent agent works, and evaluate the algorithm you chose to use. In  order to adequately defend your designs, you will need to support your  ideas with research from your readings. You must include citations for  sources that you used. Analyze the differences between human and machine approaches to solving problems.  Describe the steps a human being would take to solve this maze. Describe the steps your intelligent agent is taking to solve this pathfinding problem. What are the similarities and differences between these two approaches? Assess the purpose of the intelligent agent in pathfinding.  What is the difference between exploitation and exploration? What is  the ideal proportion of exploitation and exploration for this  pathfinding problem? Explain your reasoning. How can reinforcement learning help to determine the path to the goal (the treasure) by the agent (the pirate)? Evaluate the use of algorithms to solve complex problems.  How did you implement deep Q-learning using neural networks for this game?