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Equation 28 · Part 6 · Why Cost and Latency Belong in the Evaluation Score, Not a Footnote

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Lsequential(k)≈k lˉ,Lparallel(k)≈lˉ+ϵ(k),L_{\text{sequential}}(k) \approx k\,\bar{l}, \qquad L_{\text{parallel}}(k) \approx \bar{l} + \epsilon(k),
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What this part means

Approximately equal to; the equality is not exact.

Its job in the formula

Approximately equal to; the equality is not exact.

The passage around this formula

Start with how an agent handles its own failures. Suppose a task is retried up to k times under two different execution policies: sequential retry, where each attempt waits for the previous one to finish before starting, and parallel sampling, where all k attempts run concurrently and the first success is taken. Cost is roughly indifferent to which policy was used — the compute consumed scales with the number of attempts made, C(k) ≈\approx kcˉ\bar{c} , regardless of whether they ran one after another or all at once. Latency is not indifferent at all: Lsequential(k)≈k lˉ,Lparallel(k)≈lˉ+ϵ(k)L_{\text{sequential}}(k) \approx k\,\bar{l}, \qquad L_{\text{parallel}}(k) \approx \bar{l} + \epsilon(k). where ϵ(k)\epsilon(k) is a small scheduling and aggregation overhead that grows slowly with k . Two evaluations that both report…

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