Ψ-Efficiency Simulation in Symbolic Cognitive Agents (ERF Grounding Test)

This dataset and code present a synthetic simulation of symbolic cognitive agents undergoing entropy-aware perturbations to test the ψ-efficiency (Ψeff) metric introduced in the Entropic Recursion Framework (ERF). Ψeff quantifies the ratio of semantic information preservation to entropy-induced transformation in recursive symbolic cores over time. Agents are perturbed using symbolic noise functions and evaluated using transformer-based embeddings. This test grounds the ERF metric in measurable symbolic dynamics, supporting its use in modeling negentropic processes in cognitive systems. Simulation logs, annotated outputs, and full source code are provided for reproducibility and theoretical grounding. This work is associated with the Entropic Recursion Framework available at https://doi.org/10.5281/zenodo.15263240.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-04-22
DOI
https://doi.org/10.5281/zenodo.15265015
Primary Topic
Cognitive Computing and Networks
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Ψ-Efficiency Simulation in Symbolic Cognitive Agents (ERF Grounding Test)

Zenodo (CERN European Organization for Nuclear Research)
Cognitive Computing and Networks
article

Ψ-Efficiency Simulation in Symbolic Cognitive Agents (ERF Grounding Test)

article en

Abstract

This dataset and code present a synthetic simulation of symbolic cognitive agents undergoing entropy-aware perturbations to test the ψ-efficiency (Ψeff) metric introduced in the Entropic Recursion Framework (ERF). Ψeff quantifies the ratio of semantic information preservation to entropy-induced transformation in recursive symbolic cores over time. Agents are perturbed using symbolic noise functions and evaluated using transformer-based embeddings. This test grounds the ERF metric in measurable symbolic dynamics, supporting its use in modeling negentropic processes in cognitive systems. Simulation logs, annotated outputs, and full source code are provided for reproducibility and theoretical grounding. This work is associated with the Entropic Recursion Framework available at https://doi.org/10.5281/zenodo.15263240.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 76%
Cognitive Computing and Networks
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.