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

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