Zero-Shot Transfer with Deictic Object-Oriented Representation in Reinforcement Learning

no code implementations • NeurIPS 2018 • Ofir Marom, Benjamin Rosman

Object-oriented representations in reinforcement learning have shown promise in transfer learning, with previous research introducing a propositional object-oriented framework that has provably efficient learning bounds with respect to sample complexity.

Object reinforcement-learning +2