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Automatically evaluate, score, and visualize submitted RL agents against relevant conservation gyms

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rl-leaderboard

Automatically evaluate, score, and visualize submitted RL agents against relevant conservation gyms

How to submit an agent:

  1. Make a public github repo (see template) that contains:

    • a .zip of parameters of a SB3-trained agent; naming convention on this .zip is ENV-ALGORITHM-TEAMNAME.zip
    • a requirements.txt file that contains the packages needed to run the agent, notably gym_*
  2. Paste the link to clone this repo in this Google Form


Acknowledgements

This material is based upon work supported by the National Science Foundation under Grant DBI-1942280. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.

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Automatically evaluate, score, and visualize submitted RL agents against relevant conservation gyms

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