Abstract

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 methodologies provide well-defined processes for modeling agents, roles, goals, and interactions, yet contemporary LLM-based MAS frameworks typically lack such systematic engineering foundations. We highlight how ad hoc development practices in LLM-enhanced MAS—often driven by prompt engineering or role-playing strategies—can lead to inconsistencies and reduced maintainability. Through a critical examination of role definition, specification, and implementation, we identify several gaps in terms of software engineering. To bridge these gaps, we propose a hybrid role-based architecture where we treat roles as first-class entities at run-time encapsulating both traditional AOSE design principles and LLM-driven functionalities. By laying this groundwork, we aim to foster more robust, scalable, and transparent engineering of LLM-enhanced MAS.

Tansu Aşıcı

Ege University

A short bio here.

Önder Gürcan

Senior Researcher

My research interests include multi-agent systems, collective intelligence, self-organization and self-adaptation, simulation of biological systems, distributed clock synchronization and behavioural economics.