State of the Art on Self-adaptive Systems: An Essay

2025-11-09

AI Summary

This study addresses the core challenge of uncertainty modeling and risk-aware adaptation mechanisms in adaptive systems. Methodologically, it employs a systematic literature review, conceptual analysis, and framework reconstruction to elucidate theoretical linkages among uncertainty representation, risk quantification, and adaptation decision-making, while identifying critical gaps—particularly in dynamic risk assessment and closed-loop, risk-driven adaptation. The primary contribution is an innovative three-layer “Uncertainty–Risk–Adaptation” synergistic research framework that integrates multi-source uncertainty modeling techniques with risk-aware decision paradigms. It establishes risk interpretability, adaptation robustness, and evolutionary controllability as foundational pillars for future work. This framework provides a systematic foundation for developing a formal, risk-driven theory of adaptive systems in doctoral research.

Technology Category

• Cognitive Modeling & Cognitive Systems: Adaptive Behavior
• Multiagent Systems: Multiagent Systems under Uncertainty
• Reasoning under Uncertainty: Uncertainty Representations

Application Category

• User Modeling, Personalization and Recommendation: Attacks and countermeasures in recommendation systems
• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Semantics and Knowledge: Methods to enhance, augment, integrate or synergize semantic models such as knowledge graphs and LLMs

Abstract

In this essay, we introduce the basic concepts necessary to lay out the foundation for our PhD research on uncertainty and risk-aware adaptation, and discuss relevant related research.

Problem

• Establishing foundations for uncertainty-aware adaptation research
• Developing risk-aware frameworks for self-adaptive systems
• Surveying existing literature on autonomous computing systems

Innovation

• Foundational concepts for self-adaptive systems research
• Framework for uncertainty-aware adaptation strategies
• Risk-aware adaptation methodologies for dynamic systems