Keras-rl_DQN

Create a deep learning model to solve a OpenAI Gym Lunar Lander.
0.Open the Lunar Lander environment from gym
1.Build the deep learning model by keras Sequential API with Embedding and Dense layers
2.Import the Epsilon Greedy policy and Sequential Memory deque from keras-rl2's rl
3.input the model, policy, and the memory in to rl.agent.DQNAgent and compile the model and fit
4.using wrappers to record videos to check the quaily of the training: agent.test(env,nb_episodes=10,visualize=False)
5.Save the model's weight

rl-video-episode-5.mp4