Fitness Vectors
Fitness vectors make model improvement easier to compare because they show tradeoffs rather than hiding them.
Evidence dimensions
| Dimension | Question |
|---|---|
| Utility | Does the descendant improve the declared task? |
| Resource fit | Does it repay memory, latency, energy, and maintenance cost? |
| Local privacy | Can private work remain local when appropriate? |
| Novelty | Does it add a useful niche or reusable pattern? |
| Human benefit | Does it make users, teams, or reviewers stronger? |
| Lineage completeness | Can future builders reuse or audit the result? |
PROCEDURE fitness_proof(candidate)
vector <- MEASURE_FITNESS_VECTOR(candidate)
packet <- BUILD_EVIDENCE_PACKET(candidate, vector)
IF packet.demonstrates_net_benefit
RETURN NEXT_RELEASE_STAGE(packet)
END IF
RETURN ARCHIVE_AS_LEARNING(packet)
END PROCEDURERelated
Source reports used for this guide
These reports are preserved verbatim in the site archive. The guide above is an editorial synthesis and may narrow, qualify, or reorganize claims from the source material.
Implementation directivesModelBreeder v2.7.0 Positive Exploration DirectiveCurrent operating directive · 35.8 KB
Architecture and project resourcesModelBreeder Architecture and ProjectsSource report · 53.0 KB
Architecture and project resourcesModelBreeder Architecture and ResourcesSource report · 50.9 KB
Architecture and project resourcesModelBreeder Architecture and Resources Part 2Source report · 33.5 KB
Evolution lab and dashboardsExploring Ecology Dashboard ArchitectureSource report · 64.7 KB
Architecture and model mergingModel Breeder Architecture Deep DiveSource report · 76.7 KB
Architecture and runtime explorationModelBreeder Architecture ExplorationSource report · 48.9 KB
Positive mutualism and governanceMutualist Persistence — Uploaded EditionGovernance synthesis · 15.7 KB