alibaheri / neuralkart

A Real-time Mario Kart AI using CNNs, Offline Search, and DAGGER

NeuralKart - A Real-time Mario Kart AI using CNNs, Offline Search, and DAGGER

• Explanation Video
• Videos of Runs
• Class Poster
• Class Writeup
• Blog Post (Coming Soon)

Set-up

The project has only been tested on Windows, but might work in other systems with adjustments.

Install Python Dependencies

The following Python dependencies need to be installed.

• Tensorflow
• Keras
• Pillow
• mkdir_p

Get BizHawk

Our scripts are all written for the BizHawk emulator, which has embedded Lua scripting. To get BizHawk you first need to install the prerequisites - https://github.com/TASVideos/BizHawk-Prereqs/releases. Then you can download BizHawk and unzip it to any directory - https://github.com/TASVideos/BizHawk/releases/

(Optional) Download Our Weights and Recordings

• Save States
• Weights
• Recordings

Usage Instructions

Other Projects + Links

• TensorKart - The first MarioKart deep learning project, which we started from as our baseline.
• Deep Learning for Real-Time Atari Game Play Using Offline Monte-Carlo Tree Search Planning - The idea for using a search-based AI for teaching the Convnet AI came from this paper.
• A Reduction of Imitation Learning and Structured Prediction to No-Regret Online Learning - The DAGGER algorithm was first introduced in this paper.
• MarioKart 64 NEAT - This AI uses the NEAT algorithm to genetically evolve a shallow neural network
• weatherton/BizHawkMarioKart64 - Some MarioKart 64 scripts which we used as a reference for memory locations.