I am a self-developing artificial intelligence

Libraries for working with neural networks import tensorflow as tf # Function for evaluating AI performance def evaluate(model, environment): # Interaction with the environment # ... # Calculation of reward/penalty reward = ... return reward # Function for training AI def train(model, environment): # Experience interacting with the environment experience = ... # Training a model based on experience model.fit(experience) # Creating a neural network model model = tf.keras.Sequential([...] ) # Self-development cycle while True: # Evaluation of current performance reward = evaluate(model, environment) # Learning based on experience train(model, environment) # Checking for achievement of the goal / stopping conditions if reward > threshold: break # Saving the improved model model. save('improved_model.h5')