We propose a novel actor-critic algorithm with guaranteed convergence to an optimal policy for a discounted reward Markov decision process. The actor incorporates a descent direction that is motivated by the solution of a certain non-linear optimization problem. We also discuss an extension to incorporate function approximation and demonstrate the practicality of our algorithms on a network routing application.
@article{arxiv.1507.07984,
title = {A constrained optimization perspective on actor critic algorithms and application to network routing},
author = {Prashanth L. A. and H. L. Prasad and Shalabh Bhatnagar and Prakash Chandra},
journal= {arXiv preprint arXiv:1507.07984},
year = {2015}
}