Designing neural systems that implement human-like cognitive processes for flexible, general-purpose reasoning.
Current neural networks, despite their impressive capabilities, lack the structured cognitive processes that enable human-like reasoning. They process information uniformly without the specialized systems humans use for attention, memory, planning, and self-reflection. MEGAMIND's cognitive architecture research aims to bridge this gap.
Manages goals, plans actions, coordinates other modules, and maintains task context across reasoning steps. The "conductor" of cognitive processes.
Actively maintains and manipulates information relevant to current tasks. Limited capacity but highly flexible, enabling multi-step reasoning.
Selectively focuses processing on relevant information while filtering distractions. Enables efficient processing of complex inputs.
Stores and retrieves specific experiences and contexts. Enables learning from past situations and analogical reasoning.
Long-term knowledge storage with structured representations. Supports conceptual reasoning and knowledge integration.
Tracks confidence, detects errors, and knows what the system doesn't know. Essential for reliable, safe AI behavior.
A cognitive architecture is a theoretical framework and computational implementation of the structures and processes underlying intelligent behavior. It defines how perception, memory, attention, reasoning, and action work together. In MEGAMIND, our cognitive architecture provides the scaffold for general intelligence.
While transformers use uniform attention layers, MEGAMIND implements differentiated cognitive modules: a working memory system, an executive controller, episodic and semantic memory stores, and metacognitive monitors. These interact through structured pathways rather than uniform self-attention.
MEGAMIND implements attention control (selective focus), working memory (active information maintenance), executive function (goal management and planning), episodic memory (experience storage), semantic memory (knowledge representation), and metacognition (self-monitoring and uncertainty awareness).