Reinforce-select (RS) (Ling and Rush, 2017;Chen and Bansal, 2018) utilizes reinforcement learning to approximate the marginal likelihood.
it is trained to maximize a lower bound of the likelihood by applying the Jensen inequalily: The gradient to γ is approximated with Monte-Carlo sampling by applying the REINFORCE algorithm (Williams, 1992;Glynn, 1990).