Simulation Data

Simulation data is commonly used in domains such as physical systems, logistics processes, robotics environments, and financial scenarios. The goal is to reproduce situations that are costly, risky, or rare in the real world under controlled conditions. It is especially valuable for edge-case generation, policy testing, and pretraining. However, if the simulation environment differs from reality, the model may absorb those differences. For that reason, simulation data is powerful, but managing domain gap is essential.