  We introduce Lyceum, a high-performance computational ecosystem for robot
learning. Lyceum is built on top of the Julia programming language and the
MuJoCo physics simulator, combining the ease-of-use of a high-level programming
language with the performance of native C. In addition, Lyceum has a
straightforward API to support parallel computation across multiple cores and
machines. Overall, depending on the complexity of the environment, Lyceum is
5-30x faster compared to other popular abstractions like OpenAI's Gym and
DeepMind's dm-control. This substantially reduces training time for various
reinforcement learning algorithms; and is also fast enough to support real-time
model predictive control through MuJoCo. The code, tutorials, and demonstration
videos can be found at: www.lyceum.ml.
