Reinforcement Learning in MDPs with Information-Ordered Policies
This work develops an epoch-based reinforcement learning algorithm for infinite-horizon average-cost MDPs with continuous state and action spaces that exploits this order through counterfactual inference and instantiates the framework in lost-sales inventory systems with positive lead times, dual-sourcing systems gover...