Turing Award Winner Sutton Uses a 1967 Formula to Improve Streaming Reinforcement Learning

图灵奖得主Sutton新作：用一个1967年的公式，解决流式强化学习一大缺陷

Richard Sutton and coauthors proposed Intentional Updates, which derive the step size from the desired output change; Intentional AC approached SAC on MuJoCo under batch=1 streaming training without replay, while each update used about 1/140 of SAC’s FLOPs.

Why it matters: HKR-H/K/R all pass: Sutton's name, Intentional Updates, MuJoCo conditions, and 1/140 SAC FLOPs give it substance. Strong research signal, but less market-moving than a major LLM product release, so it stays in the 78–84 band.