Cognitive Memory Engine: Experimental Infrastructure for Long-Term AI Memory Systems

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Authors: Oskar Gerlicz-Kowalczuk
Cited by: 0

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