Stanford Intelligent Systems Laboratory (SISL)

Stanford Intelligent Systems Laboratory (SISL)

SISL studies robust decision-making in settings involving complex and dynamic environments where safety and efficiency must be balanced. We apply our work to challenges including autonomous driving, route planning, deep reinforcement learning, and safety and validation, addressing algorithms for efficiently deriving optimal decision strategies from high-dimensional, probabilistic representations, and establishing confidence in their safe and correct application in the real world.