Unverified50% confidenceFactExact time
SAC was proposed by Haarnoja et al. at UC Berkeley, introducing a maximum entropy framework that simultaneously maximizes the entropy of the policy while optimizing the expected cumulative reward
1
Sources
50%
Confidence
Long-term
Relevance
8/4/2026
First Seen
Sources
Related Claims
VerifiedSAC was proposed by the Berkeley team in 2018, introducing a maximum entropy framework; as an off-policy algorithm, it can reuse historical experience.76% similarUnverifiedClaude Shannon在1949年证明，若密钥的熵大于或等于消息的熵且密钥只使用一次，则方案具有完美保密性60% similarUnverifiedCross-entropy = entropy of the true distribution + KL divergence.59% similarUnverifiedThe Optimize Anything framework was released by a joint team from UC Berkeley, Stanford, and other top institutions58% similarUnverifiedThe structural risk minimization principle was proposed by Vapnik and directly gave rise to the design philosophy of support vector machines53% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/682171API
curl https://kongchang.com/api/v1/knowledge/claims/682171MCP
get_claim(id=682171)