Google Brain Team published the source code of the Dopamine framework, which allows the implementation of training with reinforcement for neural networks. The repository contains 15 Python files with documentation. The tool is based on TensorFlow, a library for machine learning.
The framework is based on the Arcade Learning Environment platform, which evaluates the performance of AI using video games. Developers also got access to sets of source data for training and tests on 60 games supported by the platform. This approach makes it possible to standardize the process of working with neural networks and to obtain reproducible results.
Dopamine supports 4 learning models: deep Q-learning, C51, Implicit Quantile Network and a simplified version of Rainbow.
Simultaneously with the placement of the source code, Google launched a website with tools to visualize the process of interacting with AI via Dopamine. The site supports work with multiple agents simultaneously, provides access to statistics, training models and planning through TensorBoard.
Pablo Samuel Castro and Marc G. Bellemare, Google Brain Team researchers expressed the hope that the flexibility and ease of use of the tool developed by their group will inspire developers to try out new ideas.
This is not Google's first step towards increasing the availability of tools for neural networks. In 2017, the company announced the launch of the project Google.ai, a project to democratize the achievements in the field of machine learning.
Get more info at GitHub.