CITS3001 Super Mario Project

1. Project Overview

In this project, you will develop AI agents to control the iconic character Mario in the classic game Super Mario Bros using the gym-super-mario-bros environment. The main objective is to implement at least two distinct AI algorithms/methods and compare their performance, strengths, and weaknesses in the context of playing the game.

You can undertake this project in teams of 2 that you select, if you are looking for a partner please reach out to your lab demonstrators by emails

1.1 Requirements

1.1.1 Gym-Super-Mario-Bros Environment Setup

• Set up the gym-super-mario-bros [2] environment on your local machine or any designated platform, see 4.2.2 Environment Creation.

1.1.2 AI Algorithm Implementations

• Choose and implement at least two AI algorithms. You may wish to consider the following: – Reinforcement Learning: Q-learning [3], TD(λ) [4] – Rule-Based AI: logic and heuristics. – Monte Carlo Tree Search (MCTS) [5]

You are welcome to use more advanced algorithms that utilise deep learning such as DQN’s [6] or Proximal Policy optimisation etc. but these are not covered in the unit and lab facilitators may not be able to assist with your implementations. These algorithms will also have to be referenced in your project report

1.2 Final Project Report

To demonstrate your understanding of your implementations you will be required to write a final project report. Your report must conform to the following guidelines

• At least 3 pages
• No longer than 5 pages
• No smaller than size 12 font

You are allowed to add appendices with extra figures and words but these may not be marked. Your report should cover the following areas:

1.2.1 Analysis

• Analyze and contrast the performance of the chosen AI methods.
• Discuss their respective strengths, weaknesses, and suitability for playing Super Mario Bros.

2. Submission Guidelines

You will be required to submit the following:

• A zip file containing the code for your agents
• Your final report as a PDF file Please ensure your code submission contains a README.md file explaining how to setup the environment for your project and how to run the two separate agents individually

3 Interviews

If markers suspect instances of plagarism or excessive reliance on ChatGPT or any external sources, a procedural measure has been established. Students found in such situations may be requested to attend an interview with their respective lab instructor. The purpose of this interview is to provide students with an opportunity to demonstrate their understanding of the project. It is worth noting that consistent attendance in laboratory sessions significantly mitigate the likelihood of being selected for an interview.