Abstract The combination of Reinforcement Learning (RL) with deep learning has led to a
series of impressive feats, with many believing (deep) RL provides a path towards generally …

Abstract Evaluations of Deep Reinforcement Learning (DRL) methods are an integral part of
scientific progress of the field. Beyond designing DRL methods for general intelligence …

The performance of modern reinforcement learning algorithms critically relieson tuning ever
increasing numbers of hyperparameters. Often, small changes ina hyperparameter can lead …

Reinforcement learning is a machine learning paradigm that allows learning through
interaction. It intertwines data collection and model training into a single problem statement …

Quantum computing has advanced rapidly throughout the past decade, both from a
hardware and software point of view. A variety of algorithms have been developed that are …