Speeding up Reinforcement Learning with Learned Models

In this master thesis, we have tried to solve two of most prominent Reinforcement Learning problems: sparse rewards and sample efficiency. The combination of Model Based Reinforcement Learning, Hindsight Experience Replay and off-policy methods is the approach we took to solve the problems.