missing-nodes-have-asymmetric-fail-semantics
IN derived (depth 1)
Missing nodes are treated asymmetrically: absent antecedents fail validation (conservative), absent outlist nodes pass (permissive), creating a "believe unless proven otherwise" default
Summary
When a required supporting fact is missing from the system, the justification fails and the dependent conclusion is withdrawn. But when a potential defeater or counterargument is missing, the system assumes there is no objection and lets the conclusion stand. This creates a default-to-believe posture where claims hold as long as nothing explicitly contradicts them, even if the contradicting node has never been created yet.
Justifications
SL — The asymmetry is consistent across all three beliefs and encodes a deliberate epistemic stance
Antecedents (all must be IN):
- missing-outlist-nodes-pass-validation — In `_justification_valid`, missing antecedent nodes cause the check to fail (node goes OUT), but missing outlist nodes pass (don't block) — an open-world default.
- sl-outlist-asymmetry — Missing antecedents invalidate a justification, but missing outlist nodes do not — this asymmetry enables "believe X unless Y" where Y may not yet exist in the network
- outlist-absent-means-out — An outlist node that doesn't exist in the network is treated as OUT (justification satisfied); absent antecedent nodes fail validation — this asymmetry makes missing counter-evidence permissive while missing supporting evidence is strict
Dependents
These beliefs depend on this one:
- absence-has-consistent-dual-semantics — Absence has deliberate, defined semantics throughout the system at two levels: structural absence (no justifications) creates premise behavior via vacuous truth over empty lists, while referential absence (missing nodes) follows conservative/permissive asymmetry — both forms of absence produce predictable behavior rather than errors or undefined state.
- tms-core-is-deterministic-and-conservative — The TMS engine produces deterministic, terminating truth maintenance through uniform pure evaluation, guaranteed convergence, and conservative asymmetric failure semantics for missing nodes.