Occupancy Model

Occupancy models aim to estimate the probability of an entity (e.g., a person, vehicle, or species) occupying a specific location or state over time. Current research focuses on improving model accuracy and efficiency using diverse approaches, including diffusion models, reinforcement learning frameworks (like occupancy-matching policy optimization), and generative models (such as semi-Markov chains). These advancements are impacting various fields, from robotics and autonomous systems (e.g., parking occupancy estimation, efficient reinforcement learning) to environmental monitoring (e.g., species distribution modeling using large citizen science datasets) and resource management (e.g., identifying breaches in short-term rental regulations).