Study reduces real-world sample complexity for reinforcement learning.
problem Decrease real-world sample complexity in reinforcement learning.
method Formulates a theoretical framework for Sim-to-Real reinforcement learning using ROMDPs.
result Establishes real-world sample complexity guarantees smaller than direct learning.