Show HN: PPO agent reduces elevator wait times by 84% vs. classical dispatching
Built a custom RL environment in Python/Gymnasium to benchmark PPO against a Destination Dispatching algorithm. 20 floors, 4 elevators, probabilistic traffic patterns with morning/evening rush simulation. Key result: 84% reduction in average passenger wait ti…
Comparing a classical Destination Dispatching algorithm against a PPO-trained reinforcement learning agent in a custom-built Gymnasium simulation environment. Stack: Python · Gymnasium · stable-base… [+14145 chars]