arXiv:1801.00690cs.AI
DeepMind Control Suite
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Abstract
The DeepMind Control Suite is a set of continuous control tasks with a standardised structure and interpretable rewards, intended to serve as performance benchmarks for reinforcement learning agents. The tasks are written in Python and powered by the MuJoCo physics engine, making them easy to use and modify. We include benchmarks for several learning algorithms. The Control Suite is publicly available at https://www.github.com/deepmind/dm_control . A video summary of all tasks is available at http://youtu.be/rAai4QzcYbs .
This work has two really interesting contributions, in my opinion. 1. Creating a few data points (3) for scaling laws (Figure 8). These behave similar to language models, as gwern puts it [1], but across three data points, it's a bit tough to draw a power-law conclusion…
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