Multi-Agent Decision Framework: A Systematic Approach to Agent Architecture Selection |
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| © 2025 by IJCTT Journal | ||
| Volume-73 Issue-5 |
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| Year of Publication : 2025 | ||
| Authors : Jay Prakash Thakur, Ananya Ghosh Chowdhury | ||
| DOI : 10.14445/22312803/IJCTT-V73I5P105 | ||
How to Cite?
Jay Prakash Thakur, Ananya Ghosh Chowdhury, "Multi-Agent Decision Framework: A Systematic Approach to Agent Architecture Selection," International Journal of Computer Trends and Technology, vol. 73, no. 5, pp. 27-40, 2025. Crossref, https://doi.org/10.14445/22312803/IJCTT-V73I5P105
Abstract
Artificial intelligence system architects must choose between single-agent and multi-agent architectural patterns because this selection impacts performance, resource allocation, and operational efficiency. Despite the widespread adoption of agent-based systems across different domains, no standardized framework would help guide the essential architectural choice between single-agent and multi-agent systems. This paper presents a robust, quantitative decision framework that measures and organizes the evaluation between single-agent and multi-agent architectures. The research introduces noble evaluation tools and assessment procedures that examine task features, resource limitations, performance benchmarks and domain requirements. The proposed framework demonstrates its effectiveness through case studies in multiple application domains to guide optimal agent architecture selection. The research offers practitioners and researchers a systematic approach to choose the optimal architecture to enhance system performance for specific use cases while maximizing resource utilization.
Keywords
Multi-agent systems, Artificial intelligence, Decision framework, System architecture, Agent coordination, Task decomposition.
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