Agile Methodology and AI in Multi-Agent Systems: Experimental Evaluation of an Architecture for Sprint Planning and Execution
DOI:
https://doi.org/10.5753/reic.2026.7182Keywords:
Multi-Agent Systems, Agile Methodology, Scrum, N8N, Sprint Planning, AIAbstract
This paper presents an experimental study of a Multi-Agent System (MAS) architecture integrated with the N8N platform to optimize administrative and managerial processes in agile methodologies, specifically Scrum. The architecture addresses challenges like sprint planning and resource allocation, using the Bart technique for requirements elicitation and AI-based agents for customizable workflows. This extended version validates the original proposal by comparing three implementation models (TextClassifier, Sub-agents, and Webhook) through a robust simulation study across varied complexity scenarios. Experimental results demonstrate that the Webhook model provides superior scalability and adaptability, automating task prioritization and assignment, thereby reducing the cognitive load on Scrum Masters and Product Owners.
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