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Article Type

Research Article

Abstract

In era of advanced intelligent revolutions, the collaboration between intelligent technologies became imperative. For instance, integrating 6G communications with agentic artificial intelligence considered a catalyst to shift agriculture sector into optimized and intelligence sector. This integration resulted in transitioning the sector from static automation to autonomous, agent-based ecosystems. Accordingly, the efficiency roles for artificial intelligence agents (AIAs), deploying and selecting optimal AIA is important. Yet, selection process is still difficult because agricultural criteria are multifaceted and there are inherent environmental uncertainties. To address these challenges and bolster the selection process, this paper suggests a hybrid multi-criteria decision-making (MCDM) that bolstered through integrating with uncertainty technique of Q-rung Orthopair Fuzzy Sets (Q-ROFS). The Entropy and the Simple Additive Weighting (SAW) of MCDM are used to obtain criteria weights and rank alternatives of AIAs. The proposed framework utilizes Q-ROFS to effectively represent uncertainty in expert assessments via membership, non-membership, and hesitation degrees. The Entropy method is used to objectively determine the importance of evaluation criteria based on data variability, eliminating subjective bias. Then, the SAW technique is applied to compute the overall performance scores and rank the available alternatives in a clear and efficient way. To confirm the framework's applicability, a practical case study in smart farming was conducted involving multiple criteria, alternatives, and decision makers. The findings demonstrate that the proposed approach effectively determines the most suitable alternative, with A4 achieving the highest performance score, while A3 ranked lowest. Overall, the integration of Q-ROFS, Entropy, and SAW provides an effective decision-support tool capable of handling uncertainty and complexity in modern smart agriculture systems.

Keywords

6G networks, Agentic AI, Smart agriculture, Q-rung orthopair fuzzy sets (Q-ROFS), Multi-criteria decision making (MCDM), Entropy method, Simple additive weighting (SAW)

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