# Convergence of gradient descent Monte Carlo Control with function approximation

Can anyone point me in the direction of a formal proof of convergence for a (on/off policy) Monte Carlo control algorithm with (non-)linear function approximation?

Also papers I have been able to find either consider the prediction case or TD-learning. Am I missing something or is it somehow a trivial extension of the prediction case? Are the sources I mentioned contradicting and if so, why?