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


Article Information

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

Authors: Muhammad Furqan Khan, Wasim Ahmad Khan, Muhammad Muzaffar Hameed, Arslan Ahmad Siddiqi

Journal: Sustainable Business and Society in Emerging Economies (SBSEE)

HEC Recognition History
Category From To
Y 2024-10-01 2025-12-31
Y 2023-07-01 2024-09-30
Y 2021-07-01 2022-06-30

Publisher: Center for Sustainability Research and Consultancy Pakistan

Country: Pakistan

Year: 2025

Volume: 7

Issue: 2

Language: en

DOI: 10.26710/sbsee.v7i2.3356

Keywords: fuzzy logicSelf-awareness mechanismTop-down attentionPriority-based systemBusiness agent

Categories

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.


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