A Fixed-Population Psychitectural Agent System for Lossless Compression Exploration

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Authors: Jeremy Turner
Cited by: 0

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