Laura Nolling

A Survey on Reproducibility by Evaluating Deep Reinforcement Learning Algorithms on Real-World Robots

As reinforcement learning (RL) achieves more success in solving complex tasks, more care is needed to ensure that RL research is reproducible and that algorithms therein can be compared easily and fairly with minimal bias. RL results are, however, notoriously hard to reproduce due to the algorithms’