Artificial Intelligence, Machine Learning, Data Science, Reinforcement Learning, Deep Learning.
epsilon*=0.99 # Run the episode while True: count+=1 ep_len+=1 action = 2*actor.predict(np.array(state).reshape(-1,3),verbose=0)[0] action = ddpg_add_exploration_noise(exploration_noise, action, noise_scale=0.1) next_state, reward, done, _ = env.step(action) done = 1 if done else 0 print('reward