bsuite is a research framework developed by Google DeepMind that provides a comprehensive collection of experiments for evaluating the core capabilities of reinforcement learning (RL) agents. Its main goal is to identify, measure, and analyze fundamental aspects of learning efficiency and generalization in RL algorithms. The library enables researchers to benchmark their agents on standardized tasks, facilitating reproducible and transparent comparisons across different approaches. Each experiment in bsuite is meticulously designed to capture key challenges in RL, such as exploration, credit assignment, and stability. The framework supports automated logging and analysis, generating standardized output compatible with Jupyter notebooks for streamlined evaluation. It also integrates easily with existing RL libraries and can be used locally or via cloud computing platforms, including Google Cloud.
Features
- Collection of well-designed reinforcement learning benchmark experiments
- Automated evaluation and logging for reproducible research
- Compatibility with Jupyter notebooks for visualization and analysis
- Supports Python 3.6 and 3.7 with simple installation from PyPI
- Integrates with OpenAI Gym environments using a utility wrapper
- Includes baseline agents and scripts for running experiments locally or on Google Cloud