Involving humans directly for the benefit of AI agents' training is getting traction thanks to several advances in reinforcement learning and human-in-the-loop learning. Humans can provide rewards to the agent, demonstrate tasks, design a curriculum, or act in the environment, but these benefits also come with architectural, functional design and engineering complexities. We present Cogment, a unifying open-source framework that introduces an actor formalism to support a variety of humans-agents collaboration typologies and training approaches. It is also scalable out of the box thanks to a distributed micro service architecture, and offers solutions to the aforementioned complexities.
@article{arxiv.2106.11345,
title = {Cogment: Open Source Framework For Distributed Multi-actor Training, Deployment & Operations},
author = {AI Redefined and Sai Krishna Gottipati and Sagar Kurandwad and Clodéric Mars and Gregory Szriftgiser and François Chabot},
journal= {arXiv preprint arXiv:2106.11345},
year = {2021}
}