FPMCO decomposes multi-constraint RL into KL-projection sub-problems, achieving higher reward with lower computing than second-order rivals on the new SCIG robotics benchmark.
Reinforcement-learning algorithms in systems like ChatGPT or Google’s Gemini can work wonders, but they usually need hundreds of thousands of shots at a task before they get good at it. That’s why ...
Using a bunch of carrots to train a pony and rider. (Photo by: Education Images/Universal Images Group via Getty Images) Andrew Barto and Richard Sutton are the recipients of the Turing Award for ...
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