Reinforcement Learning for Experimental Sciences: Bridging the Simulation-to-Reality Gap

The workshop studies reinforcement learning in experimental science. Researchers consider small experimental budgets, delayed observations, partial information and safety constraints, connecting sequential decision methods with autonomous laboratories, robotics, environmental sensing and digital twins. Session: 08:30–18:15 (Europe/Paris). A paid NeurIPS virtual pass includes workshop livestreams; on-site access follows the host-location registration rules.