pith:S4SNUP32
Unweighted ranking for value-based decision making with uncertainty
Unweighted fuzzy ranking proves consistent for value-based decisions without arbitrary weights.
arxiv:2605.13601 v1 · 2026-05-13 · cs.AI · cs.MA
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Claims
We mathematically prove the consistency of the Rankzzy for any admissible configuration selected by stakeholders. The evaluation conducted indicates a reduced computational cost in large-scale value-based decision-making problems and a strong rank performance regarding existing approaches when employing the aggregation via Pythagorean means.
That the fuzzy domain of decision variables together with the score function can faithfully encode both quantitative and qualitative criteria without loss of information or introduction of new bias that would invalidate the unweighted generalization.
FUW-VBDM reframes value-based decision making as unweighted optimization over a fuzzy score domain, solved via the Rankzzy method whose consistency is proven for any admissible stakeholder configuration, with lower computational cost than weighted baselines.
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Receipt and verification
| First computed | 2026-05-18T02:44:22.924486Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
9724da3f7a2d6fe04476abe77a812cead12436ce8b5c4ac805d2171d246c00ee
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· · · · ·Agent API
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curl -sH 'Accept: application/ld+json' https://pith.science/pith/S4SNUP32FVX6ARDWVPTXVAJM5L \
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Canonical record JSON
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