Car Reinforcement Learning (live demo)
Reinforcement learning (car demo)
Architecture & Working⚙️
- The neural network: Neural network is implemented using equations rather than layered sequential structures
- The optimizer: Optimizer works by randomly searching different parameter combinations till the car drives to the finish line.
How to use💻
- Just run the program and see how the car learns. You don't need to do anything
- Firstly, the car will try different combinations of parameters. Once it can drive to the finish line using a specific parameter combination, the car will then stop training and drive through the path repeatedly and slowly
😊If you would like to donate money for this work, please leave a comment to let me know😊
Thanks for trying this project
note: This project can not be considered a complete demo of reinforcement learning since it does not include mechanisms such as reward, penalty, etc. This is just a random exploration of parameters.
Status | Prototype |
Platforms | HTML5 |
Rating | Rated 5.0 out of 5 stars (1 total ratings) |
Author | Project_Unplayed |
Genre | Educational |
Made with | Godot |
Tags | 2D, artificial-intelligence, Godot, Indie, machine-learning, neural-network, random-search-optimizer, reinforcement-learning, Top-Down, Vehicles |
Code license | MIT License |
Average session | A few seconds |
Languages | English |
Accessibility | One button |
Comments
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nice!