# kaal:claim:7456999-026

**Claim.** Peer prediction is stronger than RLRF on truthful reporting because it can make honesty an equilibrium without observing ground truth.

**Type.** condition  **Support.** argued

**Holds when.**

- comparison of truthful assessment incentives

**Source quote.**

> Peer prediction (Miller, Resnick, and Zeckhauser 2005) and the Bayesian Truth Serum (Prelec 2004) pay assessors in a way that makes honest reporting an equilibrium without ever observing ground truth. This is the closest prior work to RLRF’s incentive claim, and it is stronger than RLRF on that point, since it does not require outcomes to resolve at all.

**From.** Wulf A. Kaal, *Reinforcement Learning from Reputation Feedback* (2026), II.D The Nearest Literatures, and What Is Left Over, page 9

**Cite as.** Wulf A. Kaal, Reinforcement Learning from Reputation Feedback (2026). SSRN: https://ssrn.com/abstract=7456999

**Verify.** sha256 of source PDF `01016fbbcc25cad205cebd59ea686d8dfee8ae9b632095d86ba6c9a900456a4b` at https://raw.githubusercontent.com/wulfkaal/Academic-Papers/main/papers/pdf/Kaal%20-%202026%20-%20Reinforcement%20Learning%20from%20Reputation%20Feedback.pdf

**Topics.** economics, reputation, risk-and-incentives

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