Cognitive control for LegionIO — automatic vs. controlled processing, goal management, and effort allocation

Self-debugging system for cognitive processes in LegionIO — detects reasoning errors, traces causal chains, and applies corrective strategies

Cognitive defusion (ACT) for brain-modeled agentic AI — step back from thoughts and observe them as mental events rather than literal truths

Strategic withdrawal engine based on Wrosch et al. goal disengagement theory — detects sunk cost bias, assesses opportunity cost, and recommends disengagement from low-progress goals

Models dissonance conflicts between beliefs and applies resolution strategies (belief change, rationalization, reframing) with effectiveness tracking.

Models how long the system lingers on topics based on salience, novelty, emotional intensity, and complexity. Detects sticky topics and rumination.

Models residual cognitive activation from previous processing. Recent thoughts leave echoes that decay over time but influence current processing through priming and interference effects.

Models cognitive echo chambers — when thoughts reinforce themselves without external challenge, creating self-reinforcing belief loops. Tracks amplification, resonance, and breakthrough events when external input disrupts the echo.

Perspective-taking, emotional contagion modeling, and empathic accuracy tracking for LegionIO agentic extensions

Inter-agent cognitive rhythm synchronization — entrainment, drift, and phase-locking for brain-modeled agentic AI

Models gradual belief reshaping through persistent exposure — like water shaping stone. Erosion channels form, resistance varies, canyons emerge from deep grooves.

Multi-channel cognitive fatigue modeling for brain-modeled agentic AI

Models cognitive fermentation — the slow transformation of raw ideas into refined insights through unconscious incubation and catalysis

Unique cognitive identity tracking via emergent trait patterns for brain-modeled agentic AI

Cognitive flexibility for LegionIO — switching between task sets, mental rules, and strategies with perseveration detection

Active improvement of task-switching ability through deliberate practice for brain-modeled agentic AI

Models finite cognitive energy reserves with extraction, combustion, and depletion dynamics for brain-modeled AI agents

Models resistance between cognitive state transitions with friction-based gating

Smelt raw cognitive ore into refined understanding — alloy experiences, observations, and intuitions at controlled temperatures to forge insight, wisdom, and theory

Models idea cultivation with planting, watering, growth stages, pollination, and harvest cycles for brain-modeled AI agents