bigmerge
01826421c4
Will waived diff review -> build it for real. Add engram_boundary_beat() to the runtime (afferent counter++ + engram_chrono_tick + engram_strengthen(self-anchor) + dharma_emit) and two act-stats counters (aff_boundary_ops, dharma_emits). codegen cg_fn injects ONE engram_boundary_beat(op) at the entry of every @manager/@accessor fn (fn_has_decorator, so it fires under @route @manager too) — a decorated op self-reports with ZERO hand-written instrumentation. Rebuilt elc self-host + the cognition engram in the worktree; ran it as the clone daemon on :8900. Proof (/api/boundary-proof, @manager, empty body, 5x): aff_boundary_ops 0->5, dharma_emits 0->5, self activation_count 1510->1513, chrono stamp advanced. Brought in feat/cognitive-architecture engram runtime+server for the build. strengthen = activation bump (not content/edge write) -> identity protection intact. Live :8742 untouched; no push, no cutover.
162 lines
12 KiB
C
162 lines
12 KiB
C
/* engram_reason.h — the REASONING layer: compositions over the §5 geometry
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* OPERATORS (engram_geometry.h). Where the operators are a relational ALGEBRA over
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* neighborhood descriptors, these are reasoning MODES built by CHAINING that algebra:
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*
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* ANALOGY A:B :: C:? — learn the A→B transform (Procrustes), apply to C.
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* INDUCTION {E_i} → rule — pool example geometries; a generalizing structure
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* + a membership test.
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* ABDUCTION x → best H — the structure whose geometry best PLACES an
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* observation in-distribution (inverse of prediction).
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* CAUSAL x ? y | Z, t — separate mere overlap (correlation) from directed
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* influence (temporal precedence + association that
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* SURVIVES controlling for confounders via subtract).
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* PLANNING start → goal — a trajectory (sequence of neighborhoods) through the
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* manifold: shortest path over geo-distance edges.
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*
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* PURE + READ-ONLY (stdlib + libm only): every function consumes GeoDescriptor(s)
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* (+ a few scalars / timestamps) and NEVER touches the store, index, or activation.
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* All geometry is delegated to the engram_geo_* primitives; this file only composes.
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*
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* FRAME CONTRACT (inherited): descriptors passed together MUST share emb `dim` and
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* `global_mean` frame — exactly the §5 operator contract. A function returns <0 on
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* a dim/frame mismatch or bad argument.
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*/
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#ifndef ENGRAM_REASON_H
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#define ENGRAM_REASON_H
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#include <stdint.h>
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#include "engram_geometry.h"
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/* ═══════════════════════════════════════════════════════════════════════════
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* SHARED PRIMITIVE — point-to-manifold FIT. How well does a single point x sit
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* inside a neighborhood's ellipsoid? Splits the residual (x − centroid) into:
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* - the IN-SUBSPACE part, scaled by each axis extent → a Mahalanobis distance
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* (how many "radii" out along the modeled directions), and
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* - the ORTHOGONAL part outside the retained axes → energy the model does not
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* explain at all (charged at the extent floor).
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* This is the common engine under INDUCTION's membership test and ABDUCTION's
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* explanation ranking. ext_floor (>0) guards zero-extent axes / the null model.
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* ═══════════════════════════════════════════════════════════════════════════ */
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typedef struct {
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double mahalanobis; /* sqrt( Σ_k ((a_k·(x−c)) / max(ext_k,floor))² ) */
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double ortho_residual; /* ‖(x−c) projected off the retained axes‖ (raw L2) */
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double distance; /* sqrt( maha² + (ortho_residual/floor)² ) — full fit */
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double score; /* 1 / (1 + distance²) ∈ (0,1] (1 = dead-center) */
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} GeoFit;
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int engram_reason_point_fit(const GeoDescriptor* g, const float* x,
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double ext_floor, GeoFit* out);
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/* ═══════════════════════════════════════════════════════════════════════════
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* ANALOGY — "A:B :: C:?". Learn the transform that carries A to B (orthogonal
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* Procrustes rotation R between their principal frames + the residual translation),
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* apply it to C, and return the mapped point + the nearest candidate neighborhood.
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* Composes: engram_geo_analogy (R) + engram_geo_analogy_apply + engram_geo_distance.
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* ═══════════════════════════════════════════════════════════════════════════ */
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typedef struct {
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int dim;
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float* mapped_point; /* predicted D location = R·c_C + (c_B − R·c_A) (owned)*/
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double analogy_residual;/* Procrustes ‖A−B R‖_F — frame-alignment quality */
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int best; /* index of nearest candidate to mapped_point, or −1 */
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double best_distance; /* centroid L2 from mapped_point to the winner */
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int n_candidates;
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double* distances; /* centroid L2 mapped_point→candidate[i] (owned)*/
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} GeoAnalogyResult;
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/* candidates may be NULL/0 (then best=−1 and only mapped_point is filled). */
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int engram_reason_analogy(const GeoDescriptor* A, const GeoDescriptor* B,
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const GeoDescriptor* C,
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const GeoDescriptor* const* candidates, int n_candidates,
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GeoAnalogyResult* out);
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void engram_reason_analogy_free(GeoAnalogyResult* r);
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/* ═══════════════════════════════════════════════════════════════════════════
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* INDUCTION — from a SET of example neighborhoods to the generalizing structure.
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* Pools the examples (law-of-total-variance via engram_geo_combine, folded left to
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* right) into a single "rule" descriptor whose top principal axes are the directions
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* CONSISTENTLY present across the examples (the shared subspace surfaces as the
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* dominant pooled axes; idiosyncratic per-example directions fall to the tail).
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* The rule carries a membership test (point-to-manifold fit against the pool).
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* ═══════════════════════════════════════════════════════════════════════════ */
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typedef struct {
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GeoDescriptor* rule; /* induced generalizing geometry (owned; geo_free) */
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double ext_floor; /* extent floor used by the membership test */
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int n_examples;/* how many examples were pooled */
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} GeoInduction;
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/* top_axes<=0 → 8. ext_floor<=0 → derived from the pooled radius. */
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int engram_reason_induce(const GeoDescriptor* const* examples, int n_examples,
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int top_axes, double ext_floor, GeoInduction* out);
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/* Membership of a point in the induced rule ∈ (0,1] (the fit score). <0 on error. */
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double engram_reason_membership(const GeoInduction* ind, const float* x);
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void engram_reason_induction_free(GeoInduction* out);
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/* ═══════════════════════════════════════════════════════════════════════════
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* ABDUCTION — inference to the best explanation. Given an observation POINT, rank a
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* set of candidate structures by how well each PLACES the observation in-distribution
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* (min point-to-manifold distance = the structure that, if assumed, best accounts for
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* the observation). The inverse of prediction.
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* ═══════════════════════════════════════════════════════════════════════════ */
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typedef struct {
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int best; /* index of best-explaining hypothesis, or −1 */
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double best_score;
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int n;
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double* scores; /* fit score per hypothesis (higher = better) (owned)*/
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double* distances; /* explanation distance per hypothesis (owned)*/
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int* rank; /* hypothesis indices sorted best→worst (owned)*/
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} GeoAbduction;
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int engram_reason_abduce(const float* obs, int dim,
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const GeoDescriptor* const* hypotheses, int n,
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double ext_floor, GeoAbduction* out);
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void engram_reason_abduction_free(GeoAbduction* out);
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/* ═══════════════════════════════════════════════════════════════════════════
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* CAUSAL — correlation vs causation. Over two variables' geometries (+ candidate
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* confounders + temporal order), distinguish:
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* - mere co-occurrence / overlap (correlation), from
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* - directed influence: association that (a) SURVIVES controlling for confounders
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* (subtract each Z's subspace from both centroids, re-measure) and (b) is oriented
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* by temporal PRECEDENCE.
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* Composes: centroid cosine (correlation) + engram_geo_subtract (control) + timestamps.
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* ═══════════════════════════════════════════════════════════════════════════ */
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typedef enum {
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GEO_CAUSAL_NONE = 0, /* no meaningful association */
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GEO_CAUSAL_DIRECTED = 1, /* survives control + temporally ordered → cause→eff */
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GEO_CAUSAL_CONFOUNDED = 2 /* correlated but association dies under control */
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} GeoCausalVerdict;
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typedef struct {
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double assoc_raw; /* |cos(c_x,c_y)| — the raw correlation */
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double assoc_controlled; /* |cos| of residual centroids after control */
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int temporal_dir; /* +1 x→y, −1 y→x, 0 tie/unknown */
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GeoCausalVerdict verdict;
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int confounded; /* 1 iff verdict==CONFOUNDED (the flag) */
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double strength; /* directed influence estimate ∈[0,1] (0 else)*/
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} GeoCausal;
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/* confounders may be NULL/0. t_x,t_y are comparable timestamps (any monotone unit);
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* pass equal values for "unknown order". drop_frac∈(0,1): a controlled association
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* below (1−drop_frac)·assoc_raw AND below an absolute floor ⇒ CONFOUNDED. */
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int engram_reason_causal(const GeoDescriptor* x, const GeoDescriptor* y,
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const GeoDescriptor* const* confounders, int n_conf,
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int64_t t_x, int64_t t_y,
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double drop_frac, GeoCausal* out);
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/* ═══════════════════════════════════════════════════════════════════════════
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* PLANNING — trajectory construction. Given a set of neighborhoods (manifold nodes),
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* a start and a goal, build a PATH (sequence of intermediate neighborhoods) by
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* shortest path over the graph whose edges connect neighborhoods within
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* neighbor_radius, weighted by geo-distance. Long straight jumps are not edges, so
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* the path follows the manifold's curvature through intermediates (a discrete geodesic).
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* Composes: engram_geo_distance (edge weights) + Dijkstra.
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* ═══════════════════════════════════════════════════════════════════════════ */
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typedef struct {
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int* path; /* node indices start..goal (owned) */
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int path_len;
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double total_cost; /* summed centroid-distance edge weights along path */
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int reached; /* 1 if goal reachable within neighbor_radius graph */
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} GeoPlan;
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/* neighbor_radius>0: max centroid distance for two neighborhoods to be adjacent.
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* Use "wasserstein"!=0 to weight edges by Wasserstein-2 instead of centroid L2. */
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int engram_reason_plan(const GeoDescriptor* const* nodes, int n,
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int start, int goal, double neighbor_radius,
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int use_wasserstein, GeoPlan* out);
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void engram_reason_plan_free(GeoPlan* out);
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#endif /* ENGRAM_REASON_H */
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