From Boundary Crossings to Global Connectivity: A Minimal Mechanism in Structured Agent-Based Landscapes (1.0.0)
This repository contains the Python implementation of an agent-based model investigating how localized boundary-crossing dynamics generate large-scale connectivity in structured multi-attractor landscapes.
Agents evolve in a continuous two-dimensional environment composed of attractor basins. A fraction of agents exhibits exploratory higher-mobility dynamics, while the remaining agents remain locally constrained. The model analyzes how localized configurational transitions accumulate into transition networks that progressively integrate the explored state space.
The repository includes:
- the complete simulation framework,
- the experimental pipeline used in the associated paper,
- supplementary robustness analyses,
- scripts for figure generation,
- reproducibility workflows and configuration files.
The study compares multiple exploration dynamics, including random-walk exploration, interface-sensitive dynamics, novelty-biased exploration, and flat-landscape controls.
The resulting transition graphs are analyzed using network-science metrics such as graph density, connected components, and giant weakly connected components.
All simulations are fully reproducible and tested under Python 3.11.
Release Notes
Initial public release associated with the paper:
“From Boundary Crossings to Global Connectivity: A Minimal Mechanism in Structured Agent-Based Landscapes”.
This release includes:
- the complete simulation framework,
- experimental pipelines,
- supplementary analyses,
- generated figures and processed outputs,
- reproducibility documentation.
Associated Publications
Nelli, F. From Boundary Crossings to Global Connectivity: A Minimal Mechanism in Structured Agent-Based Landscapes. SocArXiv preprint. https://osf.io/
https://doi.org/10.5281/zenodo.20145382
From Boundary Crossings to Global Connectivity: A Minimal Mechanism in Structured Agent-Based Landscapes 1.0.0
Submitted by
Fabio Nelli
Published May 17, 2026
Last modified May 17, 2026
This repository contains the Python implementation of an agent-based model investigating how localized boundary-crossing dynamics generate large-scale connectivity in structured multi-attractor landscapes.
Agents evolve in a continuous two-dimensional environment composed of attractor basins. A fraction of agents exhibits exploratory higher-mobility dynamics, while the remaining agents remain locally constrained. The model analyzes how localized configurational transitions accumulate into transition networks that progressively integrate the explored state space.
The repository includes:
- the complete simulation framework,
- the experimental pipeline used in the associated paper,
- supplementary robustness analyses,
- scripts for figure generation,
- reproducibility workflows and configuration files.
The study compares multiple exploration dynamics, including random-walk exploration, interface-sensitive dynamics, novelty-biased exploration, and flat-landscape controls.
The resulting transition graphs are analyzed using network-science metrics such as graph density, connected components, and giant weakly connected components.
All simulations are fully reproducible and tested under Python 3.11.
Release Notes
Initial public release associated with the paper:
“From Boundary Crossings to Global Connectivity: A Minimal Mechanism in Structured Agent-Based Landscapes”.
This release includes:
- the complete simulation framework,
- experimental pipelines,
- supplementary analyses,
- generated figures and processed outputs,
- reproducibility documentation.