Memory as Ontology: A Constitutional Memory Architecture for Persistent Digital Citizens

RSCT Certification: κ=0.550 (certified) | RSN: 0.37/0.32/0.31 | Topics:

Overview

This paper addresses topics relevant to RSCT research, specifically in the areas of machine learning and AI systems.

Key RSCT Relevance:

• Topic similarity score: 38%
• RSCT whitepaper similarity: 28%
• Combined relevance: 32%

RSCT Quality Metrics

| Metric | Value | Interpretation | |--------|-------|----------------| | κ-gate | 0.550 | Certified | | R (Relevance) | 0.375 | Direct relevance to research goals | | S (Stability) | 0.319 | Supporting context and patterns | | N (Noise) | 0.306 | Irrelevant components | | Gate Reached | 4 | Certification depth |

Paper Details

• Authors: Zhenghui Li
• Source: arxiv
• Primary Topic: General ML
• Difficulty: Intermediate

This review was auto-generated by the Swarm-It RSCT discovery pipeline.