I am working on a project to compare different modeling techniques for optimizing the waiting time of consumers at a movie theater. Specifically, I have created simple models using:
Discrete Event Simulation (DES)
Agent-Based Modeling (ABM)
Q-Learning based Reinforcement Learning
While the DES model produces realistic results where the waiting time changes accordingly when I modify parameters such as the number of customers and servers, the ABM and Q-Learning models do not exhibit similar behavior. In the ABM and Q-Learning models, the waiting time remains almost the same regardless of parameter changes.