PROTEUS Graph-Based Idea Evolution Through Autonomous AI Agents

This technical note presents PROTEUS, a system architecture for autonomous idea evolution in which concepts are treated as organisms within a graph-based ecology. Five specialized AI agents operate on a shared directed graph: PROMETHEUS (divergent ideation), METIS (refinement), MOMUS (adversarial critique), ANANKE (fitness-based selection and pruning), and HARMONIA (cross-branch synthesis and pattern detection). Ideas undergo mutation, crossover, selection, and fossilization through formally defined operators, with full provenance tracking enabling reconstruction of any concept’s evolutionary lineage. The architecture introduces graph-native evolution with typed cross-links (as opposed to tree-based structures), multi-parent synthesis via crossover operators, a fossil record serving as within-run memory, and ecological selection pressure through speciation with niche-specific budgets. A controlled experiment compares four conditions: human-only ideation, human–AI collaborative ideation, full autonomous multi-agent evolution, and a single-agent baseline. The experimental design encompasses 78 runs with blinded evaluation, anchored rubrics, inter-rater reliability measures, and a pre-registered statistical analysis plan. Additionally, a metapopulation architecture (KOSMOS/DAIMON) is proposed in which full-scale exploration instances spawn focused sub-instances through a biological budding mechanism, creating a two-level evolutionary dynamic grounded in metapopulation theory. Part of the DAEDALUS Cognitive AI Agent Architecture project at the University of Oradea. This document is a defensive public disclosure intended to establish prior art and timestamp the PROTEUS concept, architecture, and experimental design. It establishes priority for the following novel contributions: (a) a five-agent architecture mapping distinct evolutionary pressures (generation, refinement, critique, selection, synthesis) to specialized AI agents operating on a shared graph; (b) a formal evolutionary model with typed mutation and crossover operators, a five-dimensional fitness function, speciation with niche budgets, and a fossil record as within-run memory; (c) the KOSMOS/DAIMON metapopulation architecture implementing two-level evolution where agents handle micro-evolution within instances while humans control macro-evolution across instances through freeze-bud-compete-merge-reintroduce cycles; (d) provenance as an experimental instrument enabling full lineage reconstruction for post-hoc analysis of how ideas evolve; (e) a controlled experimental design with four conditions, pre-registered statistical analysis, blinded evaluation, and reproducible run-bundle format; and (f) the principle of resource allocation as selection pressure (investment strategy rather than rate limiting).

Authors

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-02-11
DOI
https://doi.org/10.5281/zenodo.18613922
Primary Topic
Evolutionary Algorithms and Applications
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

PROTEUS Graph-Based Idea Evolution Through Autonomous AI Agents

Dumitru-Cristian Leu
Zenodo (CERN European Organization for Nuclear Research)
Evolutionary Algorithms and Applications
article

PROTEUS Graph-Based Idea Evolution Through Autonomous AI Agents

Dumitru-Cristian Leu
article en

Abstract

This technical note presents PROTEUS, a system architecture for autonomous idea evolution in which concepts are treated as organisms within a graph-based ecology. Five specialized AI agents operate on a shared directed graph: PROMETHEUS (divergent ideation), METIS (refinement), MOMUS (adversarial critique), ANANKE (fitness-based selection and pruning), and HARMONIA (cross-branch synthesis and pattern detection). Ideas undergo mutation, crossover, selection, and fossilization through formally defined operators, with full provenance tracking enabling reconstruction of any concept’s evolutionary lineage. The architecture introduces graph-native evolution with typed cross-links (as opposed to tree-based structures), multi-parent synthesis via crossover operators, a fossil record serving as within-run memory, and ecological selection pressure through speciation with niche-specific budgets. A controlled experiment compares four conditions: human-only ideation, human–AI collaborative ideation, full autonomous multi-agent evolution, and a single-agent baseline. The experimental design encompasses 78 runs with blinded evaluation, anchored rubrics, inter-rater reliability measures, and a pre-registered statistical analysis plan. Additionally, a metapopulation architecture (KOSMOS/DAIMON) is proposed in which full-scale exploration instances spawn focused sub-instances through a biological budding mechanism, creating a two-level evolutionary dynamic grounded in metapopulation theory. Part of the DAEDALUS Cognitive AI Agent Architecture project at the University of Oradea. This document is a defensive public disclosure intended to establish prior art and timestamp the PROTEUS concept, architecture, and experimental design. It establishes priority for the following novel contributions: (a) a five-agent architecture mapping distinct evolutionary pressures (generation, refinement, critique, selection, synthesis) to specialized AI agents operating on a shared graph; (b) a formal evolutionary model with typed mutation and crossover operators, a five-dimensional fitness function, speciation with niche budgets, and a fossil record as within-run memory; (c) the KOSMOS/DAIMON metapopulation architecture implementing two-level evolution where agents handle micro-evolution within instances while humans control macro-evolution across instances through freeze-bud-compete-merge-reintroduce cycles; (d) provenance as an experimental instrument enabling full lineage reconstruction for post-hoc analysis of how ideas evolve; (e) a controlled experimental design with four conditions, pre-registered statistical analysis, blinded evaluation, and reproducible run-bundle format; and (f) the principle of resource allocation as selection pressure (investment strategy rather than rate limiting).

Zenodo (CERN European Organization for Nuclear Research)
University of Oradea (RO)
Openalex Percentile: Top 60%
Evolutionary Algorithms and Applications
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.