Reinforcement Learning · advanced · concept 187 of 311 · Updated Nov 4, 2026

🎮Sim-to-Real Transfer

Training RL agents in simulation and deploying them in the real world. Overcomes the cost and danger of real-world training. Domain randomization helps bridge the gap between sim and reality. The wider framing is physical AI: models trained largely in simulated worlds and digital twins before they ever touch hardware.