# Discrete models of continuous behavior of collective adaptive systems

arXiv: https://arxiv.org/abs/2205.00828 · HTML: https://mlsanity.com/paper/2205.00828/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 1 of its 12 references that are in the map.
- First posted on arXiv 26 Apr 2022.

## Builds on (most cited first, 1 of 1)

- [Modelling service-oriented systems and cloud services with Heraklit](https://mlsanity.com/paper/2009.14040/) (2020)

## Built on by (most cited first, 1 of 1)

- [XABPs: Towards eXplainable Autonomous Business Processes](https://mlsanity.com/paper/2507.23269/) (2025)

## Abstract (arXiv)

Artificial ants are "small" units, moving autonomously on a shared, dynamically changing "space", directly or indirectly exchanging some kind of information. Artificial ants are frequently conceived as a paradigm for collective adaptive systems. In this paper, we discuss means to represent continuous moves of "ants" in discrete models. More generally, we challenge the role of the notion of "time" in artificial ant systems and models. We suggest a modeling framework that structures behavior along causal dependencies, and not along temporal relations. We present all arguments by help of a simple example. As a modeling framework we employ Heraklit; an emerging framework that already has proven its worth in many contexts.