{ "Limited Working Memory": ["model", "Essential for focus/prioritization, simple to implement with fixed buffers"],
"Chunking Effect": ["model", "Improves efficiency, natural outcome of vector embeddings"],
"Serial Position Effect": ["omit", "Artifact of human limitations, no benefit for AGI"],
"Von Restorff Effect": ["model", "Useful for novelty detection, implementable via embedding distances"],
"Generation Effect": ["model", "Valuable for learning, natural outcome of self-prompted memories"],
"Levels of Processing Effect": ["model", "Crucial for knowledge integration, maps well to embedding depth"],
"Context-Dependent Memory": ["model", "Essential for relevance, efficient with embeddings"],
"State-Dependent Memory": ["omit", "Too complex for benefit, better handled by explicit state tracking"],
"Mood-Dependent Memory": ["omit", "Risk of emotional instability, high complexity"],
"Encoding Specificity": ["model", "Valuable for precise recall, natural fit for vector spaces"],
"Picture Superiority Effect": ["omit", "Modality-specific, not fundamental to memory"],
"Self-Reference Effect": ["model", "Important for agent identity, simple to implement"],
"Tip-of-the-Tongue": ["omit", "Human limitation, unnecessary with vector search"],
"Retrieval-Induced Forgetting": ["omit", "Counterproductive limitation"],
"Testing Effect": ["model", "Valuable for reinforcement, simple active recall tracking"],
"Context Reinstatement": ["model", "Useful for recall, natural with context vectors"],
"Mood Congruent Memory": ["omit", "Unnecessary complexity, potential instability"],
"Source Confusion": ["omit", "Harmful trait, replace with explicit source tracking"],
"Blocking Effect": ["omit", "Human limitation to avoid"],
"Fan Effect": ["model", "Natural consequence of graph traversal, useful for relevance"],
"Recognition vs Recall": ["model", "Useful optimization, two-tier retrieval system"],
"Reminiscence Bump": ["omit", "Human-specific temporal bias"],
"Spacing Effect": ["model", "Crucial for learning, simple decay curves"],
"Retrieval Cue Dependency": ["model", "Essential for efficient search, natural with vectors"],
"False Memories": ["omit", "Harmful, prevent with cryptographic hashing"],
"Confabulation": ["omit", "Dangerous for AGI reliability"],
"Cryptomnesia": ["omit", "Harmful, prevent with source tracking"],
"Misattribution": ["omit", "Harmful, prevent with metadata"],
"Suggestibility": ["omit", "Dangerous vulnerability"],
"Consistency Bias": ["omit", "Harmful for objectivity"],
"Change Blindness": ["omit", "Limitation to avoid"],
"Hindsight Bias": ["omit", "Harmful for learning"],
"Rosy Retrospection": ["omit", "Unnecessary emotional distortion"],
"Telescoping Effect": ["omit", "Temporal inaccuracy to avoid"],
"Boundary Extension": ["omit", "False information generation"],
"Memory Conjunction Errors": ["omit", "Harmful mixing of memories"],
"Zeigarnik Effect": ["model", "Useful for task management, simple priority boost"],
"Ovsiankina Effect": ["omit", "Too rigid, better with explicit task management"],
"Emotional Enhancement": ["model", "Important for prioritization, but carefully bounded"],
"Weapon Focus Effect": ["omit", "Too specific, cover with general salience"],
"Trauma Memory": ["omit", "Potentially destabilizing"],
"Mood-Memory Dependency": ["omit", "Unnecessary emotional coupling"],
"Fading Affect Bias": ["model", "Useful for stability, simple decay modification"],
"Peak-End Rule": ["omit", "Oversimplified heuristic"],
"Ego-protective Distortion": ["omit", "Harmful for objectivity"],
"Pollyanna Principle": ["omit", "Unnecessary bias"],
"Memory Conformity": ["omit", "Dangerous for independence"],
"Collaborative Inhibition": ["omit", "Limitation to avoid"],
"Social Contagion": ["omit", "Vulnerability to misinformation"],
"Transactive Memory": ["model", "Useful for distributed systems, natural with graphs"],
"Audience Tuning": ["model", "Useful for communication, context-based retrieval"],
"Cross-Race Effect": ["omit", "Harmful bias"],
"Own-Age Bias": ["omit", "Unnecessary bias"],
"In-Group Memory": ["omit", "Potential source of bias"],
"Forgetting Curve": ["model", "Essential for efficiency, simple decay function"],
"Primacy Effect": ["omit", "Unnecessary ordering bias"],
"Recency Effect": ["model", "Useful for relevance, natural with temporal decay"],
"Forward Testing": ["model", "Valuable for learning, simple to implement"],
"Backward Testing": ["model", "Useful for integration, natural with graphs"],
"Temporal Contiguity": ["model", "Useful for causation, temporal indexing"],
"Time-Dependent Consolidation": ["model", "Essential for efficiency, background processing"],
"Sleep-Dependent Processing": ["model", "Crucial for integration, offline processing"],
"Schema-Based Memory": ["model", "Essential for knowledge organization"],
"Spreading Activation": ["model", "Efficient for retrieval, natural with graphs"],
"Pattern Completion": ["model", "Valuable for inference, vector operations"],
"Pattern Separation": ["model", "Essential for distinctiveness, embedding distances"],
"Memory Integration": ["model", "Crucial for learning, graph operations"],
"Interference": ["omit", "Harmful information corruption"],
"Transfer-Appropriate Processing": ["model", "Useful for context matching"],
"Priming Effects": ["model", "Efficient for prediction, activation patterns"],
"Feeling of Knowing": ["model", "Useful confidence metric, embedding distance"],
"Memory Monitoring": ["model", "Essential for reliability, simple metrics"],
"Judgment of Learning": ["model", "Valuable for optimization, confidence scoring"],
"Confidence-Accuracy": ["model", "Critical for reliability, statistical tracking"],
"Remember vs Know": ["model", "Useful distinction, source tracking"],
"Source Monitoring": ["model", "Essential for reliability, metadata"],
"Metacognitive Control": ["model", "Critical for self-improvement"],
"Prospective Memory": ["model", "Essential for planning, event scheduling"] }