TensorFlow 1.x Deep Learning Cookbook

Getting ready

We will train a linear neural network to solve the 'CartPole-v0' environment (https://github.com/openai/gym/wiki/CartPole-v0). The goal here is to balance the pole on the cart; the observation state consists of four continuous-valued parameters: Cart Position [-2.4, 2.4], Cart Velocity [-∞, ∞], Pole Angle [~-41.8º, ~41.8º], and Pole Velocity at Tip [-∞, ∞]. The balancing can be achieved by pushing the cart either to left or right, so the action space consists of two possible actions. You can see the CartPole-v0 environment space:

Now, for Q learning, we need to find a way to quantize the continuous-valued observation states. ...