kaal:claim:7456999-031

For each prompt and candidate output, RLRF selects a validation pool by verifiable random function from agents holding relevant expertise tags.

For each coordination task (prompt and candidate output ), a validation pool is selected by verifiable random function (Micali, Rabin, and Vadhan 1999) from the set of agents holding relevant expertise tags. VRF-based selection ensures that pool composition is cryptographically verifiable ex post and resistant to ex-ante manipulation by adversarial agents.

Wulf A. Kaal, Reinforcement Learning from Reputation Feedback (2026), III.A Validation Pool Architecture, p. 11
https://ssrn.com/abstract=7456999 · source PDF

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

• the proposed validation-pool architecture

designsupport: arguedai-and-agentsconsensus-and-securitygovernance-design

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