HumemAI Research
HumemAI Research explores human-like memory for AI — combining episodic (experience-based) and semantic (knowledge-based) memory models.
We study how machines can store, retrieve, and reason over structured memory graphs built from text, tables, and user interactions.
Installation
pip install humemai-research
Usage
from humemai_research.rdflib import Humemai
# or
from humemai_research.janusgraph import Humemai
Research Areas
- Episodic Memory: Representing conversations and experiences as temporal property graphs.
- Semantic Memory: Integrating user-provided or external data (e.g. Wikidata, Wikipedia) into graph, table, and vector formats.
- Memory Management: Learning what to remember, summarize, or forget across time.
- Graph-Based Reasoning: Querying and updating symbolic–neural hybrid memories.
- Reinforcement Learning & Knowledge Graphs: Using RL to induce hierarchies and explore knowledge structures.
1 maintainer
Metadata
1 maintainer
Release files for humemai-research 2.5.7
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Source distribution (sdist)
| File | Size | Uploaded | |
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| humemai_research-2.5.7.tar.gz | 37.5 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| humemai_research-2.5.7-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 79.5 kB
Release files / humemai_research-2.5.7.tar.gz
| Download URL | humemai_research-2.5.7.tar.gz |
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| Size | 37.5 kB |
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