A Fixed-Population Psychitectural Agent System for Lossless Compression Exploration
Abstract
AbstractThis document establishes prior-art and conceptual priority for a fixed-population, multi-agent compression exploration system designed for lossless compression tasks. The first intendeduse-case of this system is competitive participation in the Hutter Prize benchmark.The system instantiates a closed set of heterogeneous agents, referred to as Infonons, eachembodying a distinct psychitectural theory of compression, with strict identity stability andbounded self-improvement. This disclosure is intentionally incomplete and non-reproducible.Certain implementation details, visual assets, and operational parameters are omitted or redactedto protect ongoing research.This document is deposited for timestamping, attribution, and provenance purposes only.
Fields of Study & Subjects
Algorithms and Data Compression
Advanced Data Compression Techniques
Computability
Logic
AI Algorithms
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 11 January 2026
- Language
- EN