An AIC-based approach for articulating unpredictable problems in open complex environments
This addresses the problem of system design reliability for architects in complex domains, but it appears incremental as it builds on existing systems approaches without claiming major breakthroughs.
The paper tackled the problem of improving architects' predictive capabilities for designing dependable systems in dynamic, unpredictable environments, using an aerospace case study to demonstrate effectiveness in identifying challenges like aircraft detection.
This research paper presents an approach to enhancing the predictive capability of architects in the design and assurance of systems, focusing on systems operating in dynamic and unpredictable environments. By adopting a systems approach, we aim to improve architects' predictive capabilities in designing dependable systems (for example, ML-based systems). An aerospace case study is used to illustrate the approach. Multiple factors (challenges) influencing aircraft detection are identified, demonstrating the effectiveness of our approach in a complex operational setting. Our approach primarily aimed to enhance the architect's predictive capability.