Unverified50% confidenceDecision RuleExact time
Stopping condition design typically involves trade-offs among three categories: performance thresholds, diminishing returns detection, and hard resource limits, and mature systems often introduce multiple mechanisms simultaneously with different priority levels assigned.
1
Sources
50%
Confidence
Long-term
Relevance
7/24/2026
First Seen
Sources
提示词自动迭代新思路：会自省、会止损的 /loop 编译器模式
redditr/learnmachinelearning7/9/2026
Related Claims
UnverifiedStopping condition design typically faces four categories of trade-off mechanisms: hard resource limits, oscillation detection, performance thresholds, and diminishing returns detection — sharing the same origin as the early stopping strategy in neural network training.81% similarUnverified在实践中优先明确约束与停止条件这两个负向维度，比精心描述正向目标更能快速压制冗余输出78% similarUnverifiedStopping conditions for the agent loop include a maximum number of reasoning iterations, time limits, token budget, tool call failure, confidence threshold, and explicit human approval.74% similarUnverified终止条件设计不当会导致无限循环（反复调用工具无法收敛）或过早终止（信息不足时就回复）两类故障73% similarUnverifiedOverly lenient stopping conditions cause agents to continue ineffective iterations on sufficiently good results, wasting computing resources, while overly strict conditions may cause the loop to never terminate.72% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/608365API
curl https://kongchang.com/api/v1/knowledge/claims/608365MCP
get_claim(id=608365)