Trace of change: How stigmergy maps social learning loops in Companion Modeling through participatory simulation
Year: 2025
Type: article
Abstract: This study explored integrating stigmergy in Companion Modeling (ComMod) to enhance social learning loops (SLL) in participatory natural resource management. Taking a case study from the Ferlo region of Senegal, the research focuses on how stigmergy – a concept derived from biology involving indirect coordination through environmental traces – stimulates and documents cognitive, normative, and relational changes among stakeholders. By leaving digital traces during the iterative development of an Agent-Based Model (ABM), stigmergy support participants in co-constructing the model representing local agro-sylvo-pastoral dynamics. The paper highlights the role of stigmergy in fostering trust, knowledge sharing, and collaboration among diverse stakeholders and research team in a ComMod process, helping to refine the collective strategies aimed at sustainable land management. This research showed that stigmergic imprints can be used as a tool for monitor how learning and model development evolve during iterative modeling workshops, contributing to more adaptive and resilient resource governance strategies. • Introduces stigmergy as a tool to trace social learning in participatory modeling. • Integrates stigmergy to enhance collaboration in Companion Modeling frameworks. • Maps stakeholder interactions using stigmergy. • Shows how stigmergy-driven simulations can strengthen community-based resource management. • Advances the understanding of collaborative learning through simulation feedback loops.
Institutions: Centre de Coopération Internationale en Recherche Agronomique pour le Développement, Université de Montpellier, Institut Sénégalais de Recherches Agricoles, Systèmes d’élevage méditerranéens et tropicaux, Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement, Université Alioune Diop de Bambey, Unité de Modélisation Mathématique et Informatique des Systèmes Complexes, Institut de Recherche pour le Développement
Language: English
Field: Decision Sciences
Domain: Social Sciences
Open Access status: hybrid
Estimated APC paid: $3,750
OpenAlex ID: W4409806350