<link rel="stylesheet" href="styles.f3b1fba60ec7970c.css">

Using LLM Agents for Strategic Goals Extraction and Decision-Making

dc.contributor.authorHADEG Mohamed Abdelmalek
dc.contributor.authorDJAGHET Mohamed
dc.contributor.authorRAHIM Messaoud (Supervised)
dc.contributor.authorRAFA Tahar (Co-supervised)
dc.date.accessioned2026-10-12T09:13:28Z
dc.date.available2026-10-12T09:13:28Z
dc.date.issued2026
dc.description.abstractStrategic planning is vital for organizations, but drafting institutional strategies and aligned unit-level goals is complex. Large Language Models (LLMs) can support this through language understanding and generation, though direct use risks unsupported, misaligned, or overly automated decisions. This project presents StratAI, a web application developed as a supervised LLM-agentbased decision-support system for institutional strategy drafting and administrative-unitlevel strategic goal derivation. The system is designed around an architecture in which LLM-based capabilities are used inside controlled stages rather than as fully autonomous decision-makers
dc.identifier.citationApplied Artificial Intelligence
dc.identifier.urihttps://dspace.univ-medea.dz/handle/123456789/14525
dc.language.isoen
dc.relation.ispartofseriesM62635; M62635
dc.titleUsing LLM Agents for Strategic Goals Extraction and Decision-Making
dc.typeLearning Object

Files

Original bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
Mémoire Finale_Djaghet mohamed_Hadeg mohamed abdelmalek.pdf
Size:
9.36 MB
Format:
Adobe Portable Document Format

License bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed upon to submission
Description: