Self-Awareness Mechanism for Top-down Attention using Fuzzy Logic in Sustainable Business Intelligence

Muhammad Furqan Khan, Wasim Ahmad Khan, Muhammad Muzaffar Hameed and Arslan Ahmad Siddiqi

Sustainable Business and Society in Emerging Economies, 2025, vol. 7, issue 2, 241-250

Abstract: Purpose: The self-awareness mechanism can serve as inspiration for the design of an artificial intelligence system for top-down attention, for which self-awareness plays an indispensable role. When agents receive multiple stimuli from the environment, it becomes very difficult for them to focus solely on the most important stimulus. So, a self-awareness mechanism is required to regulate attention.&Design/Methodology/Approach: This paper proposes the concept of a self-awareness mechanism utilizing fuzzy logic to modulate the selection of high-priority stimuli within a priority-based system. Utilizing a prioritization technique and fuzzy logic to identify the most important stimulus, this mechanism enhances the agent's self-awareness and self-control mechanisms.Findings: The results reveal that the self-awareness mechanism renders cognitive functions present in the human mind: expert systems can manage human legible knowledge and make inference upon it, such formulation allows to build a system that manages imprecise information, an artificial neural network-based cognitive structure that can learn, generalize, and prioritize all complications.Implications/Originality/Value: The study posits that fuzzy logic rules can be defined according to the priority of the input environment stimuli to generate a fuzzy output in the form of the most important stimulus.

Keywords: Self-awareness mechanism; Fuzzy logic; Top-down attention; Priority-based system; Business agent (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:src:sbseec:v:7:y:2025:i:2:p:241-250

DOI: 10.26710/sbsee.v7i2.3356

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