Thread by @lonzaandrea

ChatGPT for Robotics?
@Deepmind latest work: A general AI agent that can perform any task from human instructions!

Or at least those allowed in "the playhouse"

The cherry on top of this agent is its RL fine-tuning from human feedback, or RLHF. As in ChatGPT
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The base layer of the agent is trained with imitation learning and conditioned on language instructions

Initially, the agent had mediocre abilities

However, when it was fine-tuned with Reinforcement Learning and allowed to act independently, its abilities 🆙 significantly

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The authors structured the RL problem by training a Reward Model on human feedback, and then using this RW model to optimize the agent with online RL

The RW model, also called Inter-temporal Bradley-Terry (IBT), is trained to predict the preferences of sub-trajectories

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A sub-trajectory is preferred over another of the same episode if it represents a improvement toward the goal. Not preferred if it's a regression.

Does it work? Check out this example 📊
It appears to be effective

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Btw, they also augmented the loss of the IBT model with BC and contrastive SSL losses.

The BC+RL agent was trained using a "setter-replay" methodology. The environment was recreated based on some initial configs and the agent was left to interact freely & learn.

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Guess what? BC+RL performed much better than everything else

They evaluated the agent on multiple ways: offline and online, both automatically and manually
In every context the BC+RW model is the best
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Bonus point 1:
- BC + RL benefit from model scaling - Nice!

Bonus point 2:
- The agent can also be improved iteratively.
And it gets a lot better!
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Great work by the "Interactive Agents Team" at @deepmind : @arahuja @fede_carne @petko87ig @_agoldin @countzerozzz @TheGeorgePowell @santoroAI and others

Paper: arxiv.org/pdf/2211.11602…
Blog post: deepmind.com/blog/building-…
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I hope you find it useful! Bye

#deeplearning #RL #robotics #ML #AI

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