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.

StatusPrototype
PlatformsHTML5
Rating
Rated 5.0 out of 5 stars
(1 total ratings)
AuthorProject_Unplayed
GenreEducational
Made withGodot
Tags2D, artificial-intelligence, Godot, Indie, machine-learning, neural-network, random-search-optimizer, reinforcement-learning, Top-Down, Vehicles
Code licenseMIT License
Average sessionA few seconds
LanguagesEnglish
AccessibilityOne button

Comments

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(+1)

nice!