Methodological Considerations for Self-adaptive Systems: An Essay

2025-11-09

AI Summary

This study addresses the methodological gap in representing uncertainty and modeling risk perception within adaptive systems. Methodologically, it synthesizes conceptual analysis and critical literature review to distill core dimensions of adaptive decision-making, yielding a theoretically grounded model that integrates dynamism, context-sensitivity, and agent-centricity. The contributions are threefold: (1) it advances beyond static risk assessment paradigms by embedding risk perception directly into the adaptive process; (2) it identifies key methodological challenges—including ambiguous modeling boundaries, inadequate representation of feedback delays, and difficulties in multiscale coupling; and (3) it delineates three concrete research trajectories: multiscale modeling, human–machine collaborative perception validation, and empirically grounded definition of adaptive thresholds. The framework provides a scalable methodological foundation for intelligent adaptation under uncertainty.

Technology Category

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

Application Category

• User Modeling, Personalization and Recommendation: Attacks and countermeasures in recommendation systems
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions

Abstract

In this essay, we provide an overview of methodological considerations necessary to lay out the foundation for our PhD research on uncertainty and risk-aware adaptation.

Problem

• Addressing methodological considerations for self-adaptive systems
• Establishing foundation for uncertainty-aware adaptation research
• Developing framework for risk-aware adaptation methodologies

Innovation

• Methodological considerations for self-adaptive systems
• Foundation for uncertainty-aware adaptation research
• Risk-aware adaptation methodological framework