A developer spent a couple of days over his winter break training an artificial neural network to play the classic racing game Mario Kart 64 and documented his results to share what he learned in the process.
“It had been a few years since I’d done any serious machine learning, and I wanted to try out some of the new hotness (aka TensorFlow) I’d been hearing about,” said Kevin Hughes who works as a developer at Shopify.
Using a GeForce GTX 1060 GPU and the cuDNN-accelerated TensorFlow deep learning framework, Hughes trained his model on only four races on Luigi Raceway, two races on Kalimari Desert and two races on Mario Raceway. He mentioned that even with a small training set, the model was able to drive a new untrained section of the Royal Raceway (below).
Hughes’ adds that he plans on adding a reinforcement layer to the project so the AI can start to teach itself.
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AI-Generated Summary
- Shopify developer Kevin Hughes trained an artificial neural network to play Mario Kart 64 using a GeForce GTX 1060 GPU and the cuDNN-accelerated TensorFlow deep learning framework.
- The model learned from only four races on Luigi Raceway, two on Kalimari Desert, and two on Mario Raceway, yet could drive an untrained section of Royal Raceway.
- Hughes plans to add a reinforcement layer to the TensorKart project so the AI can teach itself.
Next Steps
- Read the TensorKart blog post for the full project details.
- Explore the TensorKart repository to review the code.
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