Google Dopamine
What is Google Dopamine?
Dopamine is a research framework for fast prototyping of reinforcement learning algorithms. It aims to fill the need for a small, easily grokked codebase in which users can freely experiment with wild ideas (speculative research).Why is Google Dopamine?
Reinforcement learning (RL) research has seen a number of significant advances over the past few years. These advances have allowed agents to play games at a super-human level — notable examples include DeepMind’s DQN on Atari games along with AlphaGo and AlphaGo Zero, as well as Open AI Five. Specifically, the introduction of replay memories in DQN enabled leveraging previous agent experience, large-scale distributed training enabled distributing the learning process across multiple workers, and distributional methods allowed agents to model full distributions, rather than simply their expected values, to learn a more complete picture of their world. This type of progress is important, as the algorithms yielding these advances are additionally applicable for other domains, such as in robotics .
Quite often, developing these kind of advances requires quickly iterating over a design — often with no clear direction — and disrupting the structure of established methods. However, most existing RL frameworks do not provide the combination of flexibility and stability that enables researchers to iterate on RL methods effectively, and thus explore new research directions that may not have immediately obvious benefits. Further, reproducing the results from existing frameworks is often too time consuming, which can lead to scientific reproducibility issues down the line.
So
Google created a Tensorflow-based framework that aims to provide flexibility, stability, and reproducibility for new and experienced RL researchers alike.
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