# 🐜 Computational Complexity and Energetics of the Ant Stack

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

[![DOI](https://img.shields.io/badge/DOI-10.5281%2Fzenodo.17238736-blue)](https://doi.org/10.5281/zenodo.17238736)

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## Abstract

> This paper investigates the computational complexity and energetics of the Ant Stack, a framework inspired by biological systems. It aims to provide insights into energy-aware robotics and computational co-design by analyzing the interplay between computational demands and energy efficiency.

## Keywords

`AntStack` · `complexity science` · `information theory` · `complex adaptive systems` · `ant colonies` · `non-equilibrium thermodynamics`

## Key Contributions

- Introduction of the Ant Stack as a novel framework for energy-aware robotics.
- Development of a comprehensive energy analysis methodology tailored for robotic systems.
- Identification of key design principles derived from biological systems to enhance computational efficiency.
- Empirical validation of theoretical models through real-world benchmarking against actual ant energetics.

## Methods

- Utilization of a multi-scale analysis framework for computational workload modeling.
- Implementation of an energy decomposition framework to estimate energy consumption.
- Application of real-time complexity analysis to evaluate computational constraints.
- Integration of uncertainty quantification techniques to enhance model reliability.

## 🎯 Consulting & Tutoring

**Available for AI Research Consulting and Tutoring.** [Contact Daniel Ari Friedman, PhD](https://danielarifriedman.com/) for collaboration on Active Inference, Bayesian modeling, and computational biology.

## Citation

```bibtex
@article{2025_AntStackComplexity,
  author = {Daniel A. Friedman},
  title = {{Computational Complexity and Energetics of the Ant Stack}},
  journal = {Zenodo},
  year = {2025},
  doi = {10.5281/zenodo.17238736},
}
```

## File Inventory

- `AGENTS.md` (1,757 bytes)
- `2025_AntStackComplexity.pdf` (2,682,615 bytes)
- `README.md` (1,361 bytes)
- `SKILL.md` (1,718 bytes)