Name
Abstract | ||
|---|---|---|
Attractors of network dynamics represent the long-term behaviours of the modelled system. Understanding the basin of an attrac-tor, comprising all those states from which the evolution will eventually lead into that attractor, is therefore crucial for understanding the response and differentiation capabilities of a dynamical system. Building on our previous results [2] allowing to find attractors via Petri net Un-foldings, we exploit further the unfolding technique for a backward exploration of the state space, starting from a known attractor, and show how all strong or weak basins of attractions can be explicitly computed. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1007/978-3-030-60327-4_17 | CMSB |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Stefan Haar | 1 | 85 | 14.63 |
| Loïc Paulevé | 2 | 204 | 18.68 |
| Stefan Schwoon | 3 | 2 | 2.11 |