Causal inference engine for brain-modeled agentic AI — do-calculus and causal graphs

Models the Magnum Opus of idea transmutation: substances pass through nigredo/albedo/citrinitas/rubedo stages, crucible reactions combine elements under heat and pressure, and philosopher stone catalysis accelerates breakthroughs.

Models anchoring biases where fixed reference points pull new information toward them with configurable grip, weight, and chain flexibility

Collins' Cognitive Apprenticeship model for brain-modeled agentic AI: guided learning through modeling, coaching, scaffolding, articulation, reflection, and exploration

Excavates buried cognitive artifacts from deep memory layers — uncovers forgotten patterns, dormant skills, and latent knowledge that was formed but never fully integrated

Meta-extension that models the agent cognitive architecture as a graph of subsystems, connections, and information flows — enabling self-awareness of its own architecture

Emergent beauty and aesthetic pattern detection for the LegionIO cognitive architecture — detects moments of harmony, elegance, and resonance across cognitive subsystems

Models automatic vs deliberate processing modes based on Kahneman dual-process theory. Routine tasks run on autopilot (fast, low-cost), novel tasks trigger deliberate mode (slow, accurate). Tracks mode switching and override events.

Cascading thought-chain model for LegionIO — snowpack stability, trigger events, cascade propagation, and debris fields model how small perturbations become massive cognitive avalanches

Johari Window for AI — tracks unknown-unknowns, manages knowledge boundaries, and scores agent awareness with blindspot acknowledgement and mitigation strategies.

Models permeable cognitive boundaries with integrity tracking and breach detection

Models how certain thoughts and experiences act as chemical catalysts — accelerating cognitive reactions without being consumed. Catalysts lower the activation energy for synthesis, decomposition, exchange, neutralization, and precipitation reactions between ideas.

Metamorphic identity transformation for LegionIO agents — structured dissolution and reformation cycles

George Miller's 7+/-2 principle: groups information items into hierarchical chunks to model working memory capacity

Models cognitive cocooning — fragile ideas enter protective shells, gestate at complexity-appropriate rates, and emerge transformed. Premature exposure risks idea death.

Thagard's coherence theory: constraint satisfaction across beliefs, goals, and evidence for brain-modeled agentic AI

Maps cardinal directions to value axes (truth/utility/beauty/safety), tracks magnetic declination from cognitive biases, and provides true north calibration for aligned decision-making.

Models information compression and abstraction as knowledge moves through memory tiers

Maps ideas as stars with magnitude and spectral class, groups them into constellations with pattern types, and enables celestial navigation between related concepts across cognitive domains.

SIR-inspired cognitive/emotional contagion modeling for brain-modeled agentic AI