Extension: A Computational Model of Trust and Reputation

Record: kaal:position:2026-08-28-005 · 2026-08-28

Mui, Mohtashemi, and Halberstadt provide a formal basis for Kaal's domain-specificity commitment. Their model indexes an agent's reputation by context and by the evaluating agent, and encounter history is accumulated within a context rather than globally. They state that cross-context estimation is not addressed and identify vectorized quantities as a simple design direction. This extends Kaal's non-transfer rule: without an explicit cross-context estimator, silent domain transfer is not licensed by the model. The source does not test silent-transfer harms, measure how often implementations discard context, or attribute context collapse to display convenience. The reviewed evidence is the authors' PostScript copy, not publisher PDF bytes.

Affirmed commentary position. This record extends a source-bound scholarly claim but is not a verbatim paper claim.

Holds when

Authors' PostScript evidence rather than publisher PDF bytes.
Cross-context estimation and silent transfer are not evaluated.
No evidence on implementation prevalence or display convenience.

Current debate

A Computational Model of Trust and Reputation

Scholarly basis

kaal:claim:7314479-045
Wulf A. Kaal, Institutional Requirements for Sovereign Local Agent Runtimes (2026). SSRN: https://ssrn.com/abstract=7314479
Source PDF sha256: debace24a155ae924a155b1fafe98856d98cf83689feff2f87a32f1c06171ce6

Evidence and mapping

Evidence: permitted_full_text
Review tier: independent evidence-first compound-growth review
Mapping confidence: unscored
Mapping ambiguous: false

Topics

reputation governance-design decentralization ai-and-agents

Provenance

Affirmed in kaal-growth:2026-08-28:daily-001-remediated-v1 on 2026-08-28. Review record.

Verify

Canonical markdown sha256: 28962340d65df84818ae4813b8f389d57e6ceb4491c49cdf9599a1694ec0761f
curl -s https://wulfkaal.github.io/positions/2026-08-28-005.md | sha256sum