# kaal:claim:7456999-032

**Claim.** RLRF permits validators to have different objective functions and domain models, treating honest disagreement on ambiguous cases as epistemic signal and systematic deviation as a possible adversarial signal.

**Type.** mechanism  **Support.** argued

**Holds when.**

- the proposed reputation-weighted validation pool

**Source quote.**

> The mechanism does not require agents to share objective functions or domain models. Diversity of across the pool is a feature rather than a bug: under reputation-weighted aggregation, disagreement among honest agents on genuinely ambiguous cases produces measurable epistemic signal, while systematic deviation from consensus identifies adversarial behavior.

**From.** Wulf A. Kaal, *Reinforcement Learning from Reputation Feedback* (2026), III.A Validation Pool Architecture, page 11

**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.** ai-and-agents, reputation, consensus-and-security

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