---
name: "AntStackComplexity"
description: "Extending the AntStack framework, this paper examines complexity science approaches to understanding ant colony organization. We connect concepts from information theory, complex adaptive systems, and..."
tags: ["antstack", "complexity-science", "information-theory", "complex-adaptive-systems", "ant-colonies", "non-equilibrium-thermodynamics"]
domain: "Entomology"
citation: "Daniel A. Friedman (2025). *AntStackComplexity*. Entomology."
doi: "10.5281/zenodo.17238736"
---

# AntStackComplexity

**Daniel A. Friedman** (2025) · Entomology

## Context

This work addresses topics in **Entomology**: AntStack, complexity science, information theory, complex adaptive systems.

## Methods

Primary methods and techniques applied in this work:

- Field observation and behavioral assays
- Population genetics analysis

## Key Findings

Core contributions and results:

- We present a comprehensive computational complexity and energy analysis framework for the Ant Stack, an integrated biomimetic architecture for embodied artificial intelligence..
- Our investigation employs analytical models for contact dynamics physics, sparse spiking neural networks, and active inference to characterize complexity and energy consumption in real-time embodied systems operating at 100 Hz control frequencies..
- Energy efficiency has emerged as a critical constraint in embodied AI systems, yet traditional complexity analysis fails to capture the nuanced energy-performance trade-offs inherent in real-world implementations..

## Related Works

- [2016_AntGenetics](../2016_AntGenetics/)
- [2016_ForagingGene](../2016_ForagingGene/)
- [2017_MutAnts](../2017_MutAnts/)

## Validation

Verification points for this work:

- DOI: 10.5281/zenodo.17238736
- PDF SHA-256: See zenodo_record
- Pairing confidence: unknown
- Last checked: 2026-06-30T23:25:43Z

## Prerequisites

- Familiarity with AntStack, complexity science, information theory
- Background in Entomology fundamentals
- Access to source repository: N/A

## Instructions

When working with this paper:

1. Reference the DOI for citation: `10.5281/zenodo.17238736`
2. Apply methods listed in the Methods section for related analysis.
3. Validate findings against the original PDF and metadata.