Unverified50% confidenceFactExact time
PPO constrains policy updates to a neighborhood of the old policy by clipping the importance sampling ratio, approximately achieving the stability guarantees of on-policy training.
1
Sources
50%
Confidence
Long-term
Relevance
9/20/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedCISPO（Clipped Importance Sampling Policy Optimization）与 PPO 同源，通过重要性采样比值的裁剪约束策略更新幅度78% similarVerifiedThe core innovation of PPO lies in limiting the magnitude of policy updates through a clipped objective function, preventing training collapse caused by excessively large single updates.77% similarUnverifiedPPO was proposed by Schulman et al. in 2017 and constrains the policy update step size by clipping the importance sampling ratio.73% similarVerifiedPPO was proposed by OpenAI in 2017 and limits the magnitude of policy updates through a clipping mechanism, truncating gradients when the probability ratio between the new and old policies exceeds the range of 1±0.2.72% similarUnverifiedThe PPO algorithm requires computing the ratio of old policy probabilities to new policy probabilities (the importance ratio), and divergence between the two engines contaminates this ratio.72% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/937389API
curl https://kongchang.com/api/v1/knowledge/claims/937389MCP
get_claim(id=937389)