Policy Optimization for Markov Games: Unified Framework and Faster Convergence Runyu Zhang Harvard University

Policy optimization, i.e. algorithms that learn to make sequential decisions by local search on the agent's policy directly, is a widely used class of algorithms in reinforcement learning [