Deep Reinforcement Learning algorithm to defeat a human player in Air Hockey Game. This is the capstone project of Hyojeong Kim, Namki Yu and Kyungeun Kim in Hanyang University.

Using Deep Q Network

• hyper parameters

  • discount_factor = 0.99
  • learning_rate = 0.001
  • epsilon = 1.0
  • epsilon_decay_step = 9e-06
  • batch_size = 64
  • train_start = 1000

• neural network

  • 4 Layers
  • input size : 8
    • paddle_position
    • paddle_velocity
    • puck_location
    • puck_velocity
  • output size : 9
    • up, down, right, left, up_left, down_left, up_right, down_right, stop
  • hidden size : (24, 24)
  • initializer : 'he_uniform'
  • loss : 'mse'
  • optimizer : 'Adam'

Goal : Using OpenAI Gym Environment

1. Add goal area
2. Add 'stop' action
3. Change CNN to DNN