# 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).

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## 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?

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## 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.