TensorFlow.js Example: Reinforcement Learning with Mountain Car Simulation

Overview

This is a modification of this tensorflow.js subrepository, by @Caisq, to tackle the OpenAI's gym MountainCar problem: https://github.com/openai/gym/blob/master/gym/envs/classic_control/mountain_car.py

For a more graphical illustration of the problem, see: http://gym.openai.com/envs/MountainCar-v0/

Features:

• Allows user to specify the architecture of the policy network, in particular, the number of the neural networks's layers and their sizes (# of units).
• Allows training of the policy network in the browser, optionally with simultaneous visualization of the cart-pole system.
• Allows testing in the browser, with visualization.
• Allows saving the policy network to the browser's IndexedDB. The saved policy network can later be loaded back for testing and/or further training.

Usage

yarn && yarn watch