Human-in-the-Loop: Enhancing Self-Adaptive Systems with User Feedback

Abstract

Self-adaptive systems are engineered to modify their operations autonomously in response to environmental changes, making them vital in dynamic computing contexts. Despite their potential, current systems often lack sufficient user interaction, which can limit their effectiveness and user satisfaction. This paper addresses this gap by introducing the Human-in-the-Loop (HITL) approach, where user feedback is systematically integrated into self-adaptive mechanisms. We employ a mixed-methods research design, combining qualitative user studies with quantitative performance analysis, to evaluate the impact of HITL on system adaptability and performance. Our key findings reveal that incorporating user feedback significantly enhances system responsiveness, accuracy, and user engagement. Moreover, HITL systems demonstrate improved fault tolerance and adaptability to unforeseen changes. This study's contributions include a novel HITL framework for self-adaptive systems and empirical evidence supporting its advantages, offering a significant advancement in the development of more resilient and user-centric adaptive technologies.