Describes continuous or quasi-continuous parameter adaptation inside a fixed structure and the requirement that it can continue after structural change freezes.
Research documentation: this page interprets a cited research source and defines evidence requirements. It does not claim a released Teleodynamic AI implementation.
Boundary
Inner dynamics change parameters inside the current hypothesis structure. They may run every eligible event and are expected to continue after outer structural actions cease.
Evidence
- Parameter revision before and after each update.
- Learning rate or natural-gradient step configuration.
- Gradient, Fisher, or other preconditioner diagnostics.
- Numerical guards and rejected updates.
- Proof that no structural identifier changed during the inner update.
Failure modes
Parameter drift, update instability, stale gradients, hidden structure changes, and unbounded adaptation must be distinguished from legitimate inner dynamics.
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?