Exploring Agentic Artificial Intelligence Systems: Towards a Typological Framework
On the map: LLM agents and tool use → General LLM agent frameworks and benchmarks
Abstract (arXiv)
Artificial intelligence (AI) systems are evolving beyond passive tools into autonomous agents capable of reasoning, adapting, and acting with minimal human intervention. Despite their growing presence, a structured framework is lacking to classify and compare these systems. This paper develops a typology of agentic AI systems, introducing eight dimensions that define their cognitive and environmental agency in an ordinal structure. Using a multi-phase methodological approach, we construct and refine this typology, which is then evaluated through a human-AI hybrid approach and further distilled into constructed types. The framework enables researchers and practitioners to analyze varying levels of agency in AI systems. By offering a structured perspective on the progression of AI capabilities, the typology provides a foundation for assessing current systems and anticipating future developments in agentic AI.
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Placed in General LLM agent frameworks and benchmarks, one of 16 directions in LLM agents and tool use. Builds on 12 of its 54 references that are in the map. First posted on arXiv 7 Jul 2025.
Builds on
12 of 54 references.
Closest ancestors · 7
Same direction, newest first
- 2024Understanding the planning of LLM agents: A survey5 Feb
- 2024Exploring Large Language Model based Intelligent Agents: Definitions, Methods, and Prospects7 Jan
- 2023Balancing Autonomy and Alignment: A Multi-Dimensional Taxonomy for Autonomous LLM-powered Multi-Agent Architectures5 Oct
- 2023An In-depth Survey of Large Language Model-based Artificial Intelligence Agents23 Sep
- 2023The Rise and Potential of Large Language Model Based Agents: A Survey14 Sep
- 2023A Survey on Large Language Model based Autonomous Agents22 Aug
- 2023Harms from Increasingly Agentic Algorithmic Systems20 Feb
Other references · 5
- 2024Agent AI: Surveying the Horizons of Multimodal Interactioncited by 170
- 2022Exploration in Deep Reinforcement Learning: A Surveycited by 166
- 2023Generative AIcited by 120
- 2017Guidelines for including grey literature and conducting multivocal literature reviews in software engineeringcited by 41
- 2024Large Model Based Agents: State-of-the-Art, Cooperation Paradigms, Security and Privacy, and Future Trendscited by 26
Built on by
Citing papers per year: 2025: 1; 2026: 2.
3 papers.
- 2025Agentic AI: A Comprehensive Survey of Architectures, Applications, and Future Directionscited by 48
- 2026Generative AI and Digital Ecosystem Resilience: A Proactive Lifecycle-Based Surveycited by 0
- 2026Who is the 'I' in AI? Establishing Decentralized Identity and Accountability for Autonomous Agentscited by 0
- 2026Who is the 'I' in AI? Establishing Decentralized Identity and Accountability for Autonomous Agents12 Oct 2026
- 2026Generative AI and Digital Ecosystem Resilience: A Proactive Lifecycle-Based Survey28 May 2026
- 2025Agentic AI: A Comprehensive Survey of Architectures, Applications, and Future Directions29 Oct 2025
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