We consider two single-item, deterministic, continuous, finite horizon inventory models having no shortage. A demand rate function, which is relatively general, for the item is assumed. In the first model, units of the item do not deteriorate; while in the second units deteriorate in a constant...

Reinforcement Learning (RL) is a learning framework in which an agent learns a policy from continual interaction with the environment. A policy is a mapping from states to actions. The agent receives rewards as feedback on the actions performed. The objective of RL is to design autonomous agents...