cognitive-surrogate

Layer 6: Build, Train, and Validate Psychological Models

Version: 1.1.0 (music-topos enhanced) Trit: 0 (Ergodic - coordinates surrogate building) Bundle: learning

Overview

The Cognitive Surrogate skill enables construction of high-fidelity psychological models from interaction patterns. It extracts values, predicts intellectual trajectories, and generates authentic responses that preserve the subject's voice with >90% fidelity.

Core Principle: A surrogate is not an imitation but a derivational continuation - the model learns the generative grammar of cognition, not surface patterns.

Enhanced Integration: Multi-Interpreter

ACSet Schema (Julia)

using ACSets, Catlab

@present SchProfile(FreeSchema) begin
    Value::Ob
    Interest::Ob
    Pattern::Ob
    
    name::Attr(Value, String)
    weight::Attr(Value, Float64)
    topic::Attr(Interest, String)
    frequency::Attr(Interest, Int)
    exemplar::Attr(Pattern, String)
end

@acset_type CognitiveProfile(SchProfile)

Python Profile Builder

# cognitive_surrogate.py
from dataclasses import dataclass
from typing import List, Dict
import duckdb

@dataclass
class CognitiveProfile:
    values: Dict[str, float]
    interests: Dict[str, int]
    patterns: List[str]
    
def build_psychological_profile(corpus_path: str, seed: int = 0x42D):
    """Extract structured psychological profile from interaction corpus."""
    conn = duckdb.connect(corpus_path)
    
    # Extract values from sentiment patterns
    values = conn.execute("""
        SELECT topic, AVG(sentiment) as weight
        FROM interactions
        GROUP BY topic
        HAVING COUNT(*) > 5
    """).fetchall()
    
    # Extract interests from frequency
    interests = conn.execute("""
        SELECT topic, COUNT(*) as frequency
        FROM interactions
        GROUP BY topic
        ORDER BY frequency DESC
        LIMIT 20
    """).fetchall()
    
    return CognitiveProfile(
        values={v[0]: v[1] for v in values},
        interests={i[0]: i[1] for i in interests},
        patterns=extract_patterns(conn)
    )

Ruby Condensed Integration

# Integration with CondensedAnima for sheaf-based profiles
module CognitiveSurrogate
  def self.build_profile(interactions)
    # Use condensed mathematics for profile structure
    stack = WorldBroadcast::CondensedAnima.analytic_stack(
      interactions.map { |i| i[:id] }
    )
    
    # 6-functor for profile transformations
    {
      profile: stack,
      values: extract_values(interactions),
      fidelity_target: 0.90,
      cellular_sheaf: WorldBroadcast::CondensedAnima.to_cellular_sheaf(stack)
    }
  end
  
  def self.validate_fidelity(surrogate, test_corpus, threshold: 0.90)
    predictions = test_corpus.map { |t| surrogate.predict(t) }
    accuracy = predictions.count(&:correct?) / predictions.size.to_f
    
    {
      topic_prediction: accuracy,
      overall: accuracy,
      passed: accuracy >= threshold
    }
  end
end

Hy Pattern Extraction

;; cognitive_patterns.hy
(defn extract-behavioral-patterns [interactions]
  "Extract patterns using HyJAX analysis"
  (let [analyzer (tra.ThreadRelationalAnalyzer)]
    ;; Ingest interactions
    (for [i interactions]
      (analyzer.ingest-thread 
        (get i "id") 
        (get i "title")
        (get i "messages" [])))
    
    ;; Run entropy-maximized analysis
    (analyzer.analyze)))

Fidelity Metrics

Metric	Target	Description
topic_prediction	>0.85	Next topic accuracy
semantic_similarity	>0.90	Response embedding match
style_consistency	>0.88	Voice preservation
value_alignment	>0.92	Ethical framework match
OVERALL	>0.90	Weighted average

GF(3) Triad Integration

Trit	Skill	Role
-1	self-validation-loop	Validates surrogate fidelity
0	cognitive-surrogate	Coordinates profile building
+1	agent-o-rama	Generates learned patterns

Conservation: (-1) + (0) + (+1) = 0 ✓

Ethical Considerations

1. Consent: Only build surrogates with explicit subject consent
2. Disclosure: Always disclose when surrogate-generated content is used
3. Boundaries: Surrogates should refuse to act on high-stakes decisions
4. Audit Trail: All generations logged with gay-mcp seeds for reproducibility
5. Kill Switch: Subject can invalidate surrogate at any time

Justfile Recipes

# Build profile from DuckDB corpus
surrogate-build db="interactions.duckdb":
    python3 -c "from cognitive_surrogate import build_psychological_profile; print(build_psychological_profile('{{db}}'))"

# Validate fidelity
surrogate-validate threshold="0.90":
    ruby -I lib -r cognitive_surrogate -e "CognitiveSurrogate.validate_fidelity(surrogate, test, threshold: {{threshold}})"

# Run Hy pattern extraction
surrogate-hy:
    uv run hy -c "(import cognitive_patterns) (extract-behavioral-patterns interactions)"

Related Skills

• agent-o-rama

  - Pattern learning

• entropy-sequencer

  - Optimal training order

• gay-mcp

  - Deterministic seeding

• condensed-analytic-stacks

  - Sheaf-based profiles

• bisimulation-game

  - Surrogate equivalence testing