Implementation of the coherence-based AGI measure introduced in
Fourati (2025), A Coherence-Based Measure of AGI.
The Coherent-AGI library provides two evaluation metrics:
A parametric mean controlling compensability across cognitive domains.
Measures coherence by integrating AGIₚ across coupling regimes.
This metric penalizes structural imbalance and brittleness across domains.
Arithmetic aggregation overstates general intelligence, because strong domains can fully compensate for collapsed ones.
AGIₚ and AGI_AUC fix this by penalizing uneven ability profiles.
Local install:
pip install -e .
from coherent_agi import agi_p, agi_auc
# Domain scores in [0,100]:
scores = [90, 100, 100, 70, 50, 0, 40, 40, 60, 30]
print("AGI_p (p=1): ", agi_p(scores, 1)) # arithmetic mean
print("AGI_p (p=0): ", agi_p(scores, 0)) # geometric mean
print("AGI_p (p=-1):", agi_p(scores, -1)) # harmonic mean
# Full coherence-based AGI:
print("AGI_AUC: ", agi_auc(scores))
If you use this library or the AGI metrics in a publication, please cite:
@article{fourati2025coherence,
title={A Coherence-Based Measure of AGI},
author={Fourati, Fares},
journal={arXiv preprint arXiv:2510.20784},
year={2025}
}