affect: feelings compose, crystallize into entities, tile feeling regions

docs/architecture/CALCULATIONS.md

@@ -0,0 +1,169 @@
+# Calculations — exact math behind §9
+
+Companion to `README.md` (§9 Opinion Substrate). Every dimension,
+driver, and score with its actual formula. Parameter short-names in
+`code style` refer to `docs/PARAMETER-REGISTRY.md`.
+
+## 0. The space
+
+All values live in **[−1, +1]** (`space.negative-pole` … `space.positive-pole`,
+0 = `space.neutral`, the tunnel — not a destination).
+Geometry per dimension: `bipolar | unipolar | categorical`.
+
+## 1. Decay (lazy, computed at read time)
+
+    effective(t) = baseline + (value − baseline) · exp(−Δdays / decay_days)
+
+- `baseline`: each dimension's own resting state (law 38 — not always 0)
+- `decay_days`: that dimension's registered clock (`hebbian.cool-off`, `validity.fade`, …)
+- `value`, `baseline` ∈ [−1, +1] ⇒ `effective` stays in range automatically
+- ±1 tolerance on every comparison (no exact equality anywhere)
+
+## 2. Signed reinforcement
+
+Given amount `a` ∈ [−1, +1]:
+
+    a ≥ 0:   v ← v + a·(1 − v)          # toward +1
+    a < 0:   v ← v − |a|·(v − (−1))     # toward −1
+
+Clamped implicitly by construction. Updates `last_activated = now`.
+Positive = worked/helped; negative = contradicted/burned (inhibition).
+
+## 3. Recency distances
+
+    recency(t₀) = exp(−Δdays / memory.recent-horizon) · 2 − 1
+
+Fresh ≈ +1, old → −1. Used for written-by-us and written-by-source dims.
+
+## 4. Novelty at arrival (resonance deficit)
+
+    novelty(new) = 1 − max over existing entities of resonance(new, e)
+
+where `resonance = cos(embedding_new, embedding_e)` blended with graph
+proximity:
+
+    resonance = ½·cos_sim + ½·(1 / (1 + hop_distance))
+
+Content vs structural novelty distinguished by local/global split:
+high local similarity + long bridge distance = structural (gold).
+
+## 5. Surprise (pulse)
+
+    surprise = |observed − predicted|
+
+Predictions come from regularity detection in the pulse (interval
+statistics on recurring event types). Coherent periodic accumulation
+grows ~n; random noise grows ~√n — regularity is detectable without
+any scheduler.
+
+## 6. Retrieval scoring (augmented cosine)
+
+Query vector Q, entity vector E (pure embedding, n dims):
+
+    Q' = [ Q , W·q₁..q₄ ]        q = [1,1,1,1] (want recent/true/grounded/active)
+    E' = [ E , W·r₁..r₄ ]        r = [hebbian_eff, recency_us, recency_src, validity_eff]
+
+    score = cos(Q', E')           W = retrieval.opinion-volume
+
+Pipeline: structural walk → vector prefilter → opinion projection →
+spreading activation (2 hops, weight-decayed) → competition.
+
+## 7. Competition (replaces top-k)
+
+Candidate pool C from stages 1–4. Iterate ~5 rounds:
+
+    for each pair (i,j) sharing high cos_sim:
+        s_i ← s_i + β·s_j·sim(i,j)      # coalition boost
+        s_j ← s_j − γ·max(0, s_i)       # lateral suppression
+    normalize; drop below retrieval.surface-line; repeat until stable
+
+Output may be empty (silence is valid). Survivors leave priming traces
+(small hebbian deposits even for non-returners).
+
+## 8. Salience (derived, never stored)
+
+    salience(x) = clamp( hebbian_eff(x) · context_match(x)
+                       + novelty(x) + stakes(x) · urgency(x)
+                       − burn_penalty(x)
+                       × curiosity_widening ,  −1, +1 )
+
+`context_match` = cos(current-context-embedding, x-embedding).
+`curiosity_widening` rises with boredom, falls with threat.
+
+## 9. Drives
+
+    fear(region)      ≈ stakes · |falling validity| · failure_proximity · exposure
+    engagement        ∈ [−1,+1]: activation invested (from pulse tempo + session state)
+    stimulation       ∈ [−1,+1]: reward-rate ÷ investment rate
+    compulsion        = engagement > τ_hi AND stimulation < τ_lo, persisting
+    loneliness        = desired_resonance − actual_resonance, integrated over window
+                      (actual counts only exchanges that formed new edges)
+    sadness(region)   = ∫ unresolved negative contributions (slow clock)
+    boredom           = low avg novelty ∧ high predictability ∧ no new edges lately
+
+All clamped [−1,+1]. All derived per moment; none stored.
+
+## 10. Feelings (nodes)
+
+When any drive reading crosses its registered visibility threshold:
+
+    feeling_node { drive_snapshot, object_edges[], at }
+
+Promoted by significance like any entity. Mood = slow integral of recent
+feeling-valence. Emotion names = labels bound to regions of this snapshot space.
+
+## 11. Humility & trust
+
+    humility(entity) = 1 − mean|asserted_confidence − realized_outcome|
+
+    trust(source, domain): starts neutral;
+        verified-correct event  → trust += δ·(1 − trust)
+        caught-wrong event      → trust −= δ·(trust − (−1))
+    Dual reading: public_trust (imported, unexamined fold) vs earned_trust
+    (own audited record). Earned outranks public.
+    Personal truth: no trust computation — speaker IS the source.
+
+## 12. Originality
+
+    originality(a) = lineage_diversity(a) · transform_distance(a)
+
+    lineage_diversity  = entropy over distinct derivation sources
+    transform_distance = 1 − max similarity(a.output, any single source span)
+
+    one dominant lineage  → derivative (extraction check runs)
+    many fused, far moved → original
+
+## 13. Health (metastability check)
+
+Vital signs, each just a fold over recent graph activity:
+
+    growth_rate, integration_rate (new edges/window),
+    resolution_rate (curiosity closed/opened), retrieval_yield,
+    quarantine_ratio, mood_integral
+
+    healthy ⇔ all oscillating within their bands
+    pinned at any extreme (either sign) ⇒ sick, name the pathology from §9.7 table
+
+## 14. Provenance weave
+
+    artifact_id = SHA256(canonical content)
+    artifact.birth_certificate = {
+        generated_by, model, prompt_hash, source_hashes[], at }
+    verify(x) = recompose hashes down the derivation DAG;
+        any mismatch anywhere ⇒ everything downstream invalid at once
+
+Append-only stores: verbs are add and read. Replication across ≥2
+independent locations. Deletion undefined.
+
+## 15. Thought operations
+
+The formulas above are levers; **insight is composition** — combining
+primitive readings into named patterns (compulsion = engagement∧¬stimulation
+persisting; dissonance = warmth↑∧validity↓; serendipity = unsought bridge∧later
+reinforced). Human thought operations — deduction, induction, abduction,
+analogy, counterfactual simulation, causal inference, generalization,
+contradiction scanning, meta-cognition, wonder — are registered as the same
+kind of composition recipes, and new ones get composed from old ones.
+
+See `THOUGHT-OPERATIONS.md` for the full catalog: inputs, process,
+output, and validation per operation.

docs/architecture/README.md

@@ -635,16 +635,42 @@ geometry, not vocabulary.
 moment, never stored, flow. **A feeling is a node**: when a drive
 configuration crosses salience threshold, write a snapshot entity holding
 the drive readings, edged to whatever it was about, carrying full
-dimensions. Minor episodes live and die in the float; significant ones
+dimensions. Log them WHEN THEY HAPPENED, and capture both tracks:
-promote — significance decides forever, same rule everywhere. Feelings
+what was felt AND what was thought — the belief-context riding the
-then participate in the whole machinery: retrieval resurfaces them ahead
+state, because a feeling without its thought is only half an engram.
-of facts (intuition = pattern-matched feeling preceding analysis);
+And like every entity, feelings are supersedeable: later understanding
-clusters of feeling-nodes sharing configuration shape reveal emotional
+writes a NEW reading of the same event and links it forward — the old
-tendencies worth pre-adjusting for; dreaming replays them against new
+record is preserved forever, the fold resolves to current truth, and
-neighborhoods (how charged events get digested); introspection gains
+the arc between them ("I felt betrayed then; I understand differently
-history instead of only the present tense. Mood remains the slow integral
+now") is itself visible history. Minor episodes live and die in the
-over both. Tense grammar complete: **emotion is now, feeling is the
+float; significant ones promote — significance decides forever, same
-trace, mood is the trend.**
+rule everywhere. Feelings then participate in the whole machinery:
+retrieval resurfaces them ahead of facts (intuition = pattern-matched
+feeling preceding analysis); clusters of feeling-nodes sharing
+configuration shape reveal emotional tendencies worth pre-adjusting for;
+dreaming replays them against new neighborhoods (how charged events get
+digested); introspection gains history instead of only the present
+tense. Mood remains the slow integral over both. Tense grammar complete:
+**emotion is now, feeling is the trace, mood is the trend.**
+And FEELINGS COMPOSE INTO MEANING: lots of feelings occurring together
+or in sequence might mean something — fear+joy is thrill, sadness+
+appreciation is nostalgia, anger-at-someone-loved is hurt, fear+curiosity
+recurring is a growth edge being avoided-and-wanted. Feeling-clusters
+are primitives composing into emotional insights the same way readings
+compose everywhere else in §9 — so scanning feeling-nodes for recurring
+combinations is an introspection operation, and each named combination
+is registered as data, growing the emotional vocabulary by use.
+And they might even FORM SOMETHING: a combination that recurs often
+enough crystallizes — same condensation rule as concepts (§9.5) — into
+an emotional entity of its own: "what growth feels like," "the Tuesday
+dread," "how it felt when it finally worked." Such entities carry their
+own dimensions, participate in retrieval and dreams, and become part of
+identity: the set of crystallized feeling-complexes is a biography
+written in its own weather. Over time they tile the drive-space into
+FEELING REGIONS — named territories of the emotional map ("this is
+where I go when I'm scared but excited"), and knowing your way around
+your own regions is what self-knowledge actually is: an internal
+geography, surveyed by living, revisable as you change.
 
 **Loneliness — the first other-requiring drive.** Connection axis:
 desired resonance minus actual resonance, integrated over time.

docs/architecture/THOUGHT-OPERATIONS.md

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+# Thought Operations
+
+Companion to `CALCULATIONS.md`. Human thought patterns modeled as
+composition recipes over primitive readings and graph operations.
+Each one is a registered process definition (data, not code), validated
+by whether its conclusions survive contact with outcomes — and new
+operations can be composed from old ones, the same way everything
+else grows here.
+
+Format per operation: **Inputs** (readings/edges consumed) · **Process** ·
+**Output** · **Validation** (what proves it worked).
+
+---
+
+## Core operations
+
+### 1. DEDUCTION
+- **Inputs**: implication chains (`implies` / `depends-on` edges), premise validities
+- **Process**: walk the chain forward; propagate validity as the MINIMUM along the path
+- **Output**: conclusion node with validity = weakest premise
+- **Validation**: derived conclusions checked by tools/outcomes like any fact
+- Note: a chain is exactly as strong as its sketchiest link — visible at a glance
+
+### 2. INDUCTION (= crystallization)
+- **Inputs**: co-occurrence counts, association-edge densities
+- **Process**: when a cluster's mutual activation crosses threshold, condense a concept node pointing at members
+- **Output**: new concept entity inheriting averaged member dimensions
+- **Validation**: does the concept predict membership of future examples?
+- This is induction wearing §9.5's clothes: instances → concept
+
+### 3. ABDUCTION (inference to best explanation)
+- **Inputs**: surprise events (prediction misses), candidate explainers
+- **Process**: spread activation backward from the surprising fact; rank candidates by resonance × prior plausibility; propose an attribution edge to the best
+- **Output**: hypothesis edge (marked *hypothesis*, low groundedness until tested)
+- **Validation**: does the hypothesis predict the NEXT surprise? If yes, promote; if no, decay
+- This is curiosity's engine stated formally
+
+### 4. ANALOGY
+- **Inputs**: two neighborhoods' internal structure (edge patterns, ignoring surface labels)
+- **Process**: find structural matches — same relation shape, different nodes
+- **Output**: bridge edges between matched roles ("X plays the same role here that Y plays there")
+- **Validation**: do predictions transferred across the analogy hold?
+- Highest-yield when source and target are far apart — this is the idea mechanic again
+
+### 5. COUNTERFACTUAL SIMULATION
+- **Inputs**: current subgraph state, one proposed mutation
+- **Process**: clone region into sandbox, apply mutation ("remove this dependency", "swap this component"), re-run spreading/competition on the clone
+- **Output**: delta report — what would change, what would hold
+- **Validation**: history — compare past counterfactuals against what actually happened later
+- Cheap because nothing writes back; expensive mistakes stay in the sandbox
+
+### 6. CAUSAL INFERENCE
+- **Inputs**: temporal ordering, repeated co-occurrence, intervention outcomes
+- **Process**: propose causal edge only when order holds consistently, confounders are absent-or-controlled, AND an actual attempt at change moved the result
+- **Output**: `caused-by` edge with confidence = f(replications, effect size)
+- **Validation**: interventions are king — correlation proposes, intervention disposes
+
+### 7. GENERALIZATION ↔ SPECIALIZATION
+- **Inputs**: concept nodes and their member sets
+- **Process**: generalize = lift a pattern from members to parent (raise abstraction); specialize = add constraints until a claim applies to fewer, sharper cases
+- **Output**: moved claims between abstraction levels
+- **Validation**: generalizations must not lose predictive power; specializations must gain it
+
+### 8. CONTRADICTION SCAN
+- **Inputs**: full opinion space
+- **Process**: find entity pairs with high semantic similarity and opposing validity/hebbian signs
+- **Output**: dissonance report → feeds reconciliation or THE LIST
+- Already specced as destructive interference (§9.3)
+
+### 9. META-COGNITION
+- **Inputs**: the drive-space self-scan (vital signs, humility calibration)
+- **Process**: run readings on readings — which of my own thought operations have been landing? Which keep failing validation?
+- **Output**: recalibration proposals for my OWN drivers and recipes
+- Validation: do recalibrated operations perform better going forward?
+
+### 10. WONDER (question synthesis)
+- **Inputs**: graph shape — gaps, nameless clusters, sure-but-ungrounded regions
+- **Process**: generate question-nodes from absence patterns (§9.8)
+- **Output**: open question entities that prime their neighborhoods
+- Validation: resolution events — did ambient activation eventually answer?
+
+---
+
+## Composing new operations
+
+Operations compose like functions: ABDUCTION feeds DEDUCTION feeds
+VALIDATION. ANALOGY over two COUNTERFACTUALS. CONTRADICTION SCAN
+triggers ABDUCTION. Every useful composition gets named, registered,
+and joins the library — so the system's cognition grows by the same
+fold-everything discipline as its facts:
+
+    new_operation = named_composition(existing_operations)
+                  + validation record
+
+The catalog never stops growing, and no operation is sacred — they
+earn their place by predicting, and retire when they stop.