Aquí tienes un ejemplo de código para crear una red neuronal en Python usando TensorFlow y Keras, diseñada para ser entrenada en el problema de resolver un cubo de Rubik:

```python
import numpy as np
import tensorflow as tf
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense, Conv2D, Flatten, Dropout

def create_rubiks_solver_model():
    model = Sequential()
    model.add(Conv2D(64, kernel_size=3, activation='relu', padding='same', input_shape=(6, 3, 3, 6)))
    model.add(Conv2D(128, kernel_size=3, activation='relu', padding='same'))
    model.add(Conv2D(256, kernel_size=3, activation='relu', padding='same'))
    model.add(Dropout(0.5))
    model.add(Flatten())
    model.add(Dense(512, activation='relu'))
    model.add(Dropout(0.5))
    model.add(Dense(256, activation='relu'))
    model.add(Dense(12, activation='softmax'))

    model.compile(optimizer='adam', loss='sparse_categorical_crossentropy', metrics=['accuracy'])
    return model

rubiks_solver = create_rubiks_solver_model()
```
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