# Self-Organization and Artificial Life

arXiv: https://arxiv.org/abs/1903.07456 · HTML: https://mlsanity.com/paper/1903.07456/

## Key facts

- Cited by 11 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 14 Mar 2019.

## Built on by (most cited first, 11 of 11)

- [Embodied Co-Design for Rapidly Evolving Agents: Taxonomy, Frontiers, and Challenges](https://mlsanity.com/paper/2512.04770/) (2025)
- [Artificial Collective Intelligence Engineering: a Survey of Concepts and Perspectives](https://mlsanity.com/paper/2304.05147/) (2023)
- [Can Media Act as a Soft Regulator of Safe AI Development? A Game Theoretical Analysis](https://mlsanity.com/paper/2509.02650/) (2025)
- [MacroSwarm: A Field-based Compositional Framework for Swarm Programming](https://mlsanity.com/paper/2401.10969/) (2024)
- [Software Engineering for Collective Cyber-Physical Ecosystems](https://mlsanity.com/paper/2406.04780/) (2024)
- [Intelligence as information processing: brains, swarms, and computers](https://mlsanity.com/paper/2108.05349/) (2021)
- [Scaling up the self-optimization model by means of on-the-fly computation of weights](https://mlsanity.com/paper/2211.01698/) (2022)
- [Evolving Neural Networks Reveal Emergent Collective Behavior from Minimal Agent Interactions](https://mlsanity.com/paper/2410.19718/) (2024)
- [Emergence in artificial life](https://mlsanity.com/paper/2105.03216/) (2021)
- [On Physical Origins of Learning](https://mlsanity.com/paper/2310.02375/) (2023)
- [Artificially intelligent agents in the social and behavioral sciences: A history and outlook](https://mlsanity.com/paper/2510.05743/) (2025)

## Abstract (arXiv)

Self-organization can be broadly defined as the ability of a system to display ordered spatio-temporal patterns solely as the result of the interactions among the system components. Processes of this kind characterize both living and artificial systems, making self-organization a concept that is at the basis of several disciplines, from physics to biology and engineering. Placed at the frontiers between disciplines, Artificial Life (ALife) has heavily borrowed concepts and tools from the study of self-organization, providing mechanistic interpretations of life-like phenomena as well as useful constructivist approaches to artificial system design. Despite its broad usage within ALife, the concept of self-organization has been often excessively stretched or misinterpreted, calling for a clarification that could help with tracing the borders between what can and cannot be considered self-organization. In this review, we discuss the fundamental aspects of self-organization and list the main usages within three primary ALife domains, namely "soft" (mathematical/computational modeling), "hard" (physical robots), and "wet" (chemical/biological systems) ALife. We also provide a classification to locate this research. Finally, we discuss the usefulness of self-organization and related concepts within ALife studies, point to perspectives and challenges for future research, and list open questions. We hope that this work will motivate discussions related to self-organization in ALife and related fields.