Physics-Informed Generative World Models for Real-Time Bidding: Deriving Statistical Laws from First Principles
Reliable policy optimization in real-time bidding (RTB) demands a high-fidelity world model capable of simulating stochastic market dynamics under constraints. However, current generative simulators are limited by their reliance on deterministic point prediction objectives (e.g., mean squared error). These approaches a...