Pearl: A Production-Ready Reinforcement Learning Agent
github.com> prioritize cumulative long-term feedback over immediate feedback and can adapt to environments with limited observability, sparse feedback, and high stochasticity
Sounds like something that could learn to play decent poker.
Sorry for the dumb question, but can someone ELI5 what one is supposed to do with this? How does it fit into the world of fine-tuning, function calling, etc?
This is not a LLM.
This is an AI in maybe the more traditional/popsci sense. A digital robot. It not just understands its perceptions (like an LLM), but it acts on that understanding to achieve its goal(s).
The reinforcement learning aspect is simply how it learns its goals. It takes a database of "good bot" / "bad bot" feedback and associated context, and implicitly learns what it should do.
Reinforcement learning is not LLM. It's the technology that is used in industrial applications (walking, acting robots, etc) and game playing (e.g. AlphaGo to play Go, AlphaChess, etc.)
unwise name
They missed spelling it 'perla' on purpose?
I'm guessing it's named after Judea Pearl.
or Prrl