Path dependence and local rationality

Explains why sample order, initialization, history, and locally selected actions can produce different final structures without implying global optimality.

Research
Last verified
2026-06-25 00:00 UTC
Updated
Reading time
1 minutes

Explains why sample order, initialization, history, and locally selected actions can produce different final structures without implying global optimality.

Research documentation: this page interprets a cited research source and defines evidence requirements. It does not claim a released Teleodynamic AI implementation.

Trajectory matters

Final structure may vary with sample order, random seed, initial resource, and early actions. Reproducibility therefore means reproducing distributions and trajectories, not demanding one identical final graph unless execution is deterministic.

Experiment matrix

  • Fixed data with shuffled order.
  • Fixed order with varied seeds.
  • Varied initial resource.
  • Replayed action trace.
  • Greedy local controller versus long-horizon or static baselines.

Claim limit

Local rationality only means the chosen action minimized the declared local objective among recorded candidates. It is not a claim of planning, foresight, or global optimality.

Scope

This starter page defines the questions, boundaries, evidence, and failure modes that should be recorded before a capability is presented as supported.

Engineering considerations

  • Identify the source, version, target environment, and owner.
  • Separate observed values from estimates and externally reported values.
  • Record trade-offs, unsupported cases, and fallback behavior.
  • Link performance statements to a compatible benchmark methodology.

Verification questions

  • What exact artifact, revision, backend, and environment were reviewed?
  • Which assumptions could change the result?
  • Which data should be retained so another engineer can reproduce the conclusion?