Large language models (LLMs) are transforming how we build multi-agent systems (MAS); yet, many LLM-centric frameworks still lack the engineering rigour that agent-oriented software engineering (AOSE) provides, resulting in systems that are powerful …

This paper presents the outcomes of an open-floor session held at the 13th International Workshop on Engineering Multi-Agent Systems (EMAS 2025), aimed at co-developing a research roadmap for the EMAS community. Participants collaboratively …

This paper proposes a structured approach to integrating Large Language Models (LLMs) into Multi-Agent Systems (MAS) by revisiting and extending the fundamental Agent-Oriented Software Engineering (AOSE) concept of "roles." Traditional AOSE …

Intelligent agents have been a cornerstone of Artificial Intelligence (AI) since its early days—and received significant attention in the 1990s when the notion of autonomous agent was established, giving rise to research on Engineering Multi-Agent …

The emergence of Large Language Models (LLMs) with increasingly sophisticated natural language understanding and generative capabilities has sparked interest in the Agent-based Modelling (ABM) community. With their ability to summarize, generate, …

We present Social Digital Twinner, an innovative social simulation tool for exploring plausible effects of what-if scenarios in complex adaptive social systems. The architecture is composed of three seamlessly integrated parts: a data infrastructure …

Alors que les grands modèles linguistiques (LLM) continuent de faire des progrès significatifs, leur meilleure intégration dans les simulations basées sur des agents offre un potentiel de transformation pour la compréhension des systèmes sociaux …

As large language models (LLMs) continue to make significant strides, their better integration into agent-based simulations offers a transformational potential for understanding complex social systems. However, such integration is not trivial and …