mlsanityData to 14 Oct 2026

Enhancing Multi-Criteria Decision Analysis with AI: Integrating Analytic Hierarchy Process and GPT-4 for Automated Decision Support

arXiv 2402.07404 ↗First posted 12 Feb 2024cs.AI cs.CR cs.MAcited by 2

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Abstract (arXiv)

Our study presents a new framework that incorporates the Analytic Hierarchy Process (AHP) and Generative Pre-trained Transformer 4 (GPT-4) large language model (LLM), bringing novel approaches to cybersecurity Multiple-criteria Decision Making (MCDA). By utilizing the capabilities of GPT-4 autonomous agents as virtual experts, we automate the decision-making process, enhancing both efficiency and reliability. This new approach focuses on leveraging LLMs for sophisticated decision analysis, highlighting the synergy between traditional decision-making models and cutting-edge AI technologies. Our innovative methodology demonstrates significant advancements in using AI-driven agents for complex decision-making scenarios, highlighting the importance of AI in strategic cybersecurity applications. The findings reveal the transformative potential of combining AHP and LLMs, establishing a new paradigm for intelligent decision support systems in cybersecurity and beyond.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 1 of its 26 references that are in the map. First posted on arXiv 12 Feb 2024.

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1 of 26 references.

References · 1

  1. 2023Exploring the Sensitivity of LLMs' Decision-Making Capabilities: Insights from Prompt Variation and Hyperparameterscited by 32

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 1; 2025: 0; 2026: 1.

2 papers.