Say we are designing a neural network for self driving cars. This question came about after seeing a video in the Machine Learning class taught by Andrew Ng at Stanford. The video uses two neural networks, one is trained to drive on single lane roads, while the other is trained to drive on two lane roads. When the prediction of one is stronger than the other, the stronger neural network is used to drive the car. This allows the car to switch from single to two lane roads (one way and two way roads).
Would one neural network be able to do this? Basically use two "systems" internally to decide the action to take? Intuitively I think somehow the neural network can do this.
Another example of this question I can think of is, predicting if it will rain in the next four hour block. We want to divide the day into six four hour blocks, and take features at each block start and predict if it will rain in the next four hours. Would six neural networks (one that works best with a start of midnight, another of 4am, another of 8am, etc...) be better than a single neural network?