GitHub / act3-ace / 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/

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Mean commits per author: 6.43
Development Distribution Score: 0.622
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Topics: evaluation-framework, reinforcement-learning, reinforcement-learning-algorithms, reinforcement-learning-environments

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