Cognitive Memory Engine: Experimental Infrastructure for Long-Term AI Memory Systems
Abstract
Cognitive Memory Engine is an experimental research project focused on developing infrastructure for persistent, long-term memory systems for artificial intelligence agents. The project explores architectural approaches enabling neural and agentic AI systems to: • store and retrieve structured knowledge • maintain episodic and semantic memory representations • evolve knowledge through reinforcement and decay mechanisms • build relational knowledge graphs • support multi-agent shared memory environments This project investigates memory persistence mechanisms inspired by cognitive science and computational neuroscience. It introduces a modular architecture combining vector databases, knowledge graphs, event-driven orchestration, and reinforcement-based memory ranking. The goal of the project is to provide an open research platform enabling experimentation with advanced AI memory architectures suitable for future autonomous AI systems. The repository currently represents an experimental and evolving infrastructure design.
Fields of Study & Subjects
AI-based Problem Solving and Planning
Cognitive Computing and Networks
Psychiatry
Mental Health
Neuroscience
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 1 February 2026
- Language
- EN