Learning Synthetic Environments and Reward Networks for Reinforcement Learning

Fabio Ferreira, Thomas Nierhoff, Andreas Saelinger +1

We introduce Synthetic Environments (SEs) and Reward Networks (RNs), represented by neural networks, as proxy environment models for training Reinforcement Learning (RL) agents. We…