Themis: An explainable AI-enabled framework for Reinforcement Learning with Human Feedback

Themis is a newly announced explainable AI framework designed for Reinforcement Learning (RL) that integrates human feedback to enhance safety and transparency. It supports over 200 environments and allows for easy configuration of experiments, demonstrating the ability to train reward models that align closely with true reward signals based on human preferences. This framework is significant for practitioners as it provides a scalable, user-friendly platform for conducting RL experiments with large participant groups while ensuring robust alignment and explainability, addressing critical challenges in RL safety.