This is how a lot of things work already. Neural nets are bad at strict logic. If you give one net one of two tasks, depending on a state, it takes a lot of tra

This is how a lot of things work already. Neural nets are bad at strict logic. If you give one net one of two tasks, depending on a state, it takes a lot of training before the learned tasks separate from each other. Ideally, the aspects unique to each task would be completely separate and anything common to both tasks would occur once in the net and get used for both. In practice, it increases training requirements by so much that you are better off creating 2 nets and logically separating them with your own code or even creating a 3rd net to detect which state you are in.