Plans turn intentions into revisable dependency graphs (migration 0027):
objective, assumptions, ordered or dependent steps, capabilities,
expected observations, preconditions, risk, estimates, budget,
completion criteria, abort conditions and the alternatives considered.
- Validation owns structure: acyclic dependencies, registered and
unlocked capabilities only, schema-valid parameters, targets that agree
with parameters, read-only checks, a closed set of step kinds and
internal actions. Model proposals are parsed into the same structure;
fields that could carry authority or claim progress are reported as
ignored, and an invalid draft is stored as a draft that never runs.
- The planner prefers deterministic strategies: a direct action verified
by observation, a read-only diagnosis that requests temporary scoped log
access with risk and fallback stated, and an escalation that diagnoses
and informs the operator instead of repeating a failed action. Failed
strategies are not reused; a model is consulted only when none applies.
- The executor holds no state in memory: it claims a step with a
conditional update, acts only through Invoke and RequestCapability, and
records the outcome. Waiting for approval or access forms a subordinate
intention and blocks the parent with the reason. Expectations become
verification predictions resolved from a read-only observation, so an
HTTP-level success is never taken as the outcome; a miss is a prediction
error that weakens the supporting belief and triggers reconsideration.
Replanning creates a new revision, withdraws open requests of the old
one and keeps it as history, within a replan limit. Checks never raise
approval prompts. Budgets stop runaway plans. Preconditions skip actions
when the world already changed. Dream plans and disabled sandbox minds
never act. An interrupted non-idempotent action with no record is
blocked for verification instead of repeated; recorded outcomes are
adopted. Completed plans are stored as procedural memories; a completed
escalation does not count as fulfilling the intention.
- Executions and approvals record their origin; minds may withdraw their
own pending approval requests; Preview reports a decision without side
effects; service.status is allowed by default as a bounded read.
Every breakdown now carries its meaning: an uncalibrated epistemic score
derived from recorded evidence, not a probability of truth. Belief detail
adds a calibrated estimate read from the mind's resolved predictions when
at least twenty were decided in the score's range, and otherwise says why
none is shown; and names the primary uncertainty deterministically (no live
evidence, conflicting evidence, second-hand only, unclear reading, a single
source family, little evidence). The belief list heading becomes Score.
Phase 9. Goals form a mind-scoped tree with kind, priority, progress and
blockers; their deterministic relevance to a candidate feeds the
goal_relevance attention feature and a goal monitor raises stalled goals
and observations that touch one. Drives are a closed set of eight
scalars with operator-configured ranges and personality-derived
baselines; there is no self-preservation, replication or acquisition
drive and no way to add one at runtime. Affect is ten scalars moved by an
explicit rule table over events and decaying towards baseline; both
modulate attention weights each cycle and the effective weights are
recorded with every cycle and shown beside the configured ones.
Predictions carry a window and machine-checkable criteria (event terms
occurring or staying absent, a belief reaching a confidence, or operator
judgement). A resolver job judges them deterministically, keeps an
append-only outcome history for calibration (accuracy, Brier score,
confidence buckets, overconfidence flag), emits prediction_error events
scaled by how confident the miss was, and feeds the outcome back into the
linked belief as evidence. Causal hypotheses derive predictions
automatically. Curiosity turns misses, contradictions and unexplained
observations into questions that compete for attention and become
investigation goals when admitted.
Brain gains after-cycle hooks and goal/motivation state. API, UI (goals,
prediction dashboard, cognitive state panel, effective weights) and CLI
(goal, prediction, state). Demo scenario 4 verified end to end.
Andy Dixon