Add a `NLPModelStopping`

[tmigot]

It is an NLPStopping that behaves like an AbstractNLPModel, it would

• update the state whenever we call NLPModel API's function
• update x if it is different than the one from the state
• we can think of updating the list of states when we update x?

This would help using non-stopping solvers.