  The RangL project hosted by The Alan Turing Institute aims to encourage the
wider uptake of reinforcement learning by supporting competitions relating to
real-world dynamic decision problems. This article describes the reusable code
repository developed by the RangL team and deployed for the 2022 Pathways to
Net Zero Challenge, supported by the UK Net Zero Technology Centre. The winning
solutions to this particular Challenge seek to optimize the UK's energy
transition policy to net zero carbon emissions by 2050. The RangL repository
includes an OpenAI Gym reinforcement learning environment and code that
supports both submission to, and evaluation in, a remote instance of the open
source EvalAI platform as well as all winning learning agent strategies. The
repository is an illustrative example of RangL's capability to provide a
reusable structure for future challenges.
