This paper introduces the Behaviour Suite for Reinforcement Learning, or bsuite for short. bsuite is a collection of carefully-designed experiments that investigate core capabilities of reinforcement learning (RL) agents with two objectives. First, to collect clear, informative and scalable problems that capture key issues in the design of general and efficient learning algorithms. Second, to study agent behaviour through their performance on these shared benchmarks. To complement this effort, we open source github.com/deepmind/bsuite, which automates evaluation and analysis of any agent on bsuite. This library facilitates reproducible and accessible research on the core issues in RL, and ultimately the design of superior learning algorithms. Our code is Python, and easy to use within existing projects. We include examples with OpenAI Baselines, Dopamine as well as new reference implementations. Going forward, we hope to incorporate more excellent experiments from the research community, and commit to a periodic review of bsuite from a committee of prominent researchers.

介绍用于强化学习的行为套件——bsuite，它是一系列经过精心设计的实验，目的在于收集和研究能够捕捉通用和高效学习算法设计核心问题的清晰、有信息量和可扩展的问题，以及通过这些共享基准测试评估代理人行为，这一库使用 Python 编写，容易嵌入现有项目，并通过 github.com/deepmind/bsuite开源。

强化学习行为套件