Models below-threshold cognitive traces that influence behavior without reaching conscious awareness in the LegionIO architecture

Detects when reality deviates from expectations using Bayesian surprise (KL divergence). Tracks habituation, generates orienting signals, and adapts sensitivity per domain.

Swarm orchestration and charter system for brain-modeled agentic AI

GitHub-specific swarm pipeline (finder/fixer/validator) for brain-modeled agentic AI

Provides time-aware cognitive processing: elapsed awareness, urgency, temporal patterns, and deadline tracking

Hyperbolic temporal discounting model for brain-modeled agentic AI planning and impulse control

Models other agents mental states — beliefs, desires, intentions — enabling perspective-taking and behavior prediction

Atomic cognitive processing cycle (11 phases, 3 modes) for brain-modeled agentic AI

Domain knowledge transfer modeling for brain-modeled agentic AI

Models individual differences in tolerance for ambiguity and uncertainty for brain-modeled agentic AI

Intention formation and drive synthesis for brain-modeled agentic AI

Short-term active maintenance of task-relevant information with capacity limits, decay, and rehearsal