title: Dopamine: A Research Framework for Deep Reinforcement Learning
abstract: Deep reinforcement learning (deep RL) research has grown significantly in recent years. A number of software offerings now exist that provide stable, comprehensive implementations for benchmarking. At the same time, recent deep RL research
  has become more diverse in its goals. In this paper we introduce Dopamine, a new research framework for deep RL that aims to support some of that diversity. Dopamine is open-source, TensorFlow-based, and provides compact yet reliable
  implementations of some state-of-the-art deep RL agents. We complement this offering with a taxonomy of the different research objectives in deep RL research. While by no means exhaustive, our analysis highlights the heterogeneity of research
  in the field, and the value of frameworks such as ours.
authors: Pablo Samuel Castro Subhodeep Moitra Carles Gelada Saurabh Kumar Marc G. Bellemare
hIndex: Marc G. Bellemare 34