Selective Memory with Hierarchical Concept Indexing for Scalable Knowledge Graphs in Autonomous Agents
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| Natura: | Recurso digital |
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Zenodo
2026
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| _version_ | 1866901944071618560 |
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| author | Head, Hank |
| author_facet | Head, Hank |
| contents | This paper presents a three-tier memory architecture that mimics human selective recall: always-loaded base knowledge for sub-millisecond responses, a hierarchical concept index for O(1) concept-to-location lookup, and bounded working memory with LRU eviction. Unlike approaches that load entire knowledge graphs at startup, this architecture maintains constant startup time (less than 100ms) and bounded memory (less than 25MB) while preserving 95% reasoning accuracy. Validation across 9 agents in 5 domains demonstrates 97,000x query speedup over full-graph loading for large corpora and 96% tier-prediction accuracy. |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_19788364 |
| institution | Zenodo |
| language | |
| publishDate | 2026 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Selective Memory with Hierarchical Concept Indexing for Scalable Knowledge Graphs in Autonomous Agents Head, Hank memory architecture knowledge graphs scalability neurosymbolic AI selective memory This paper presents a three-tier memory architecture that mimics human selective recall: always-loaded base knowledge for sub-millisecond responses, a hierarchical concept index for O(1) concept-to-location lookup, and bounded working memory with LRU eviction. Unlike approaches that load entire knowledge graphs at startup, this architecture maintains constant startup time (less than 100ms) and bounded memory (less than 25MB) while preserving 95% reasoning accuracy. Validation across 9 agents in 5 domains demonstrates 97,000x query speedup over full-graph loading for large corpora and 96% tier-prediction accuracy. |
| title | Selective Memory with Hierarchical Concept Indexing for Scalable Knowledge Graphs in Autonomous Agents |
| topic | memory architecture knowledge graphs scalability neurosymbolic AI selective memory |
| url | https://doi.org/10.5281/zenodo.19788364 |