EcoSysML: A metamodel for Socio-Ecological Systems (SES) integrating machine learning

Kane Cheikhou Akhmed, Diaw Samba, Ba Mandicou, Bah Alassane, Delay Etienne. 2025. EcoSysML: A metamodel for Socio-Ecological Systems (SES) integrating machine learning. In : Intelligent Systems and Applications : Proceedings of the 2025 Intelligent Systems Conference (IntelliSys 2025), Volume 1. Arai Kohei (ed.). Cham : Springer, 24-40. (Lecture Notes in Networks and Systems, 1553) Intelligent Systems conference (IntelliSys 2025). 11, Amsterdam, Pays-Bas, 28 Août 2025/29 Août 2025.

Résumé : Despite the growing need for formalized frameworks to model socio-ecological systems (SES), no existing approach adheres to the Object Management Group (OMG) standards for structuring and simulating their complexity. Agro-sylvo-pastoral systems exemplify SES where micro-level agent behaviors shape macro-level dynamics, while policy interventions influence local decision-making. However, existing modeling approaches lack a standardized structure to integrate artificial intelligence (AI) algorithms within agents, limiting their ability to adapt to macro-level policy changes and optimize decisions dynamically. The absence of a formal metamodel further restricts interoperability, reusability, and systematic policy evaluation in SES. In this study, we present Ecological System Modeling Language (EcoSysML), a novel metamodel for SES designed in accordance with OMG standards to formally define their structure and dynamics. A key innovation of EcoSysML is the LearningModel, which enables the seamless integration of AI-driven decision-making within agents, allowing them to learn, adapt, and optimize their strategies over time. By leveraging fundamental concepts (Actor, Activity, Resource, ExternalProcess, and PolicyProduct), the metamodel provides a coherent and structured representation of SES, explicitly defining how agents interact with their environment, manage resources, and respond to policy interventions. By bridging agent-based modeling with artificial intelligence, EcoSysML establishes a scalable, interoperable foundation for SES simulation and AI-driven policy design.

Mots-clés libres : Object Management Group (OMG) standards, Socio-ecological systems, Agent-based modeling, Machine Learning, Reinforcement Learning

Auteurs et affiliations

• Kane Cheikhou Akhmed, UCAD (SEN) - auteur correspondant
• Diaw Samba, UCAD (SEN)
• Ba Mandicou, UCAD (SEN)
• Bah Alassane, UCAD (SEN)
• Delay Etienne, CIRAD-ES-UMR SENS (SEN) ORCID: 0000-0001-6633-6269

Source : Cirad-Agritrop (https://agritrop.cirad.fr/614588/)

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