Lede: Alqithami (2026) introduces Preregistered Belief Revision Contracts that publicly fix evidence triggers, admissible revision operators, priority rules and fallback policies before deliberation begins (https://arxiv.org/abs/2604.15558).

The protocol admits only updates that cite a preregistered trigger backed by a nonempty set of externally validated evidence tokens, with non-fallback steps enforced by a router; under evidential contracts with conservative fallback, social-only rounds cannot increase confidence or generate purely conformity-driven wrong-but-sure cascades. Auditable trigger protocols admit evidential PBRC normal forms that preserve belief trajectories, and any top-hypothesis change is attributable to a concrete validated witness set. For token-invariant contracts, enforced trajectories depend solely on token-exposure traces; under flooding dissemination these traces equal truncated reachability, yielding tight diameter bounds for universal evidence closure (Alqithami, 2026). This synthesizes AGM belief revision (Alchourrón et al., 1985, https://doi.org/10.1016/0004-3702(85)90012-5) with the dynamic doxastic logic introduced in the paper.

Amodei et al. (2016) catalogued conformity and unintended multi-agent failures among concrete AI safety problems (https://arxiv.org/abs/1606.06565); the present work supplies a protocol-level countermeasure the 2016 paper did not foresee, while the original arXiv text understates computational costs of real-time router enforcement and omits cryptographic signing methods for witness tokens already standard in distributed-ledger commitment schemes. Simulations in the source illustrate cascade suppression yet reveal robustness-liveness trade-offs previously mapped in mechanism-design literature on verifiable computation.

Token-invariant PBRC therefore reduces epistemic accountability to auditable trace invariants expressible in the introduced contractual dynamic doxastic logic, supplying a formal bridge between commitment devices in game theory and scalable oversight techniques required for reliable autonomous agents.