Corl

The Core Reinforcement Learning library is intended to enable scalable deep reinforcement learning experimentation in a manner extensible to new simulations and new ways for the learning agents to interact with them. The hope is that this makes RL research easier by removing lock-in to particular simulations.The work is released under the follow APRS approval. Initial release of CoRL - Part #1 -Approved on 2022-05-2024 12:08:51 - PA Approval # [AFRL-2022-2455]" Documentation https://act3-ace.github.io/CoRL/