A Hybrid Role-Based Reference Architecture for LLM-Enhanced Multi-Agent Systems

AAMAS 2026 Workshop EMAS Submission35 Authors

Keywords: Multi-agent systems, large language models, agent-oriented software engineering, role-based architecture, software design patterns

Abstract:

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 engineer-
ing (AOSE) provides, resulting in systems that are powerful but difficult
to maintain and scale. In our previous work, we critically examined the
"role" concept across definition, specification, and implementation, and
proposed a preliminary hybrid role-based architecture where roles are
treated as first-class run-time entities that support four different action
implementation types. However, that earlier work remained at a concep-
tual level: it identified the need for typed actions and runtime roles but
did not provide a formal meta-model specifying how these constructs re-
late to one another, nor did it offer a concrete realization or validation.
Building on that foundation, this paper closes this gap by defining a role
meta-model for LLM-enhanced agents that specifies the core role con-
structs, their interfaces, constraints, and interaction relationships, with
clear variation points for design-time and run-time implementation. We
realize this meta-model as a framework-agnostic Java annotation set:
any Java-based agent framework can adopt the annotations to expose
roles, actions, and interaction points declaratively in code and validate
them at run-time. We demonstrate the applicability of our approach
by implementing a hotel reservation scenario in the SCOP framework,
where each agent type is realized through dedicated role specifications
and role implementations combining hybrid action types. Finally, we
discuss practical design considerations—deliberation–execution separa-
tion, action-type boundary decisions, and observability and debugging—
offering guidance toward production-grade LLM-enhanced MAS.

Paper Type: Regular paper

Demo: No, we do not plan to present a demo.

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Submission Number: 35