title: LLM-Agent-UMF: LLM-based Agent Unified Modeling Framework for Seamless
    Integration of Multi Active/Passive Core-Agents
summary: The integration of tools in LLM-based agents overcame the difficulties of
  standalone LLMs and traditional agents' limited capabilities. However, the
  conjunction of these technologies and the proposed enhancements in several
  state-of-the-art works followed a non-unified software architecture resulting
  in a lack of modularity. Indeed, they focused mainly on functionalities and
  overlooked the definition of the component's boundaries within the agent. This
  caused terminological and architectural ambiguities between researchers which
  we addressed in this paper by proposing a unified framework that establishes a
  clear foundation for LLM-based agents' development from both functional and
  software architectural perspectives.
    Our framework, LLM-Agent-UMF (LLM-based Agent Unified Modeling Framework),
  clearly distinguishes between the different components of an agent, setting
  LLMs, and tools apart from a newly introduced element: the core-agent, playing
  the role of the central coordinator of the agent which comprises five modules:
  planning, memory, profile, action, and security, the latter often neglected in
  previous works. Differences in the internal structure of core-agents led us to
  classify them into a taxonomy of passive and active types. Based on this, we
  proposed different multi-core agent architectures combining unique
  characteristics of various individual agents.
    For evaluation purposes, we applied this framework to a selection of
  state-of-the-art agents, thereby demonstrating its alignment with their
  functionalities and clarifying the overlooked architectural aspects. Moreover,
  we thoroughly assessed four of our proposed architectures by integrating
  distinctive agents into hybrid active/passive core-agents' systems. This
  analysis provided clear insights into potential improvements and highlighted
  the challenges involved in the combination of specific agents.
paper_authors._id: 66ef311b5e34548b973dc2bf
paper_authors.name: Amine B. Hassouna
paper_authors.status: extracted_confirmed
paper_authors.statusLastChangedAt: 2024-09-21T21:09:10.319Z
paper_authors._id: 66ef3076801ea45d7a88546a
paper_authors.avatarUrl: /avatars/81225d6302b1b0f8bbf727aa2998cd3f.svg
paper_authors.fullname: Amine Ben Hassouna
paper_authors.type: user
paper_authors.user: amine-bh
paper_authors._id: 66ef311b5e34548b973dc2c0
paper_authors.name: Hana Chaari
paper_authors._id: 66ef311b5e34548b973dc2c1
paper_authors.name: Ines Belhaj
paper_title: LLM-Agent-UMF: LLM-based Agent Unified Modeling Framework for Seamless
    Integration of Multi Active/Passive Core-Agents
paper_summary: The integration of tools in LLM-based agents overcame the difficulties of
  standalone LLMs and traditional agents' limited capabilities. However, the
  conjunction of these technologies and the proposed enhancements in several
  state-of-the-art works followed a non-unified software architecture resulting
  in a lack of modularity. Indeed, they focused mainly on functionalities and
  overlooked the definition of the component's boundaries within the agent. This
  caused terminological and architectural ambiguities between researchers which
  we addressed in this paper by proposing a unified framework that establishes a
  clear foundation for LLM-based agents' development from both functional and
  software architectural perspectives.
    Our framework, LLM-Agent-UMF (LLM-based Agent Unified Modeling Framework),
  clearly distinguishes between the different components of an agent, setting
  LLMs, and tools apart from a newly introduced element: the core-agent, playing
  the role of the central coordinator of the agent which comprises five modules:
  planning, memory, profile, action, and security, the latter often neglected in
  previous works. Differences in the internal structure of core-agents led us to
  classify them into a taxonomy of passive and active types. Based on this, we
  proposed different multi-core agent architectures combining unique
  characteristics of various individual agents.
    For evaluation purposes, we applied this framework to a selection of
  state-of-the-art agents, thereby demonstrating its alignment with their
  functionalities and clarifying the overlooked architectural aspects. Moreover,
  we thoroughly assessed four of our proposed architectures by integrating
  distinctive agents into hybrid active/passive core-agents' systems. This
  analysis provided clear insights into potential improvements and highlighted
  the challenges involved in the combination of specific agents.
paper_ai_summary: A unified framework for LLM-based agents defines clear component boundaries and proposes a taxonomy of core-agents to enhance modularity and clarify architectural aspects.
paper_ai_keywords: LLM-based agents unified modeling framework LLM-Agent-UMF core-agent modules planning memory profile action security agent taxonomy passive core-agents active core-agents multi-core agent architectures hybrid active/passive systems