Towards systems that dynamically change and evaluate abstractions
Ada Diaconescu, David King, Kirstie L. Bellman, Christopher A. Landauer, Phyllis R. Nelson · EPiC series in computing · 2024
Abstraction levels can be explicitly studied, changed and analyzed with metrics on their impact for a given problem. Also different methods for analyzing abstraction levels and their metrics can lead to different conclusions. Hence researchers usually iteratively experiment with these different methods to find the right abstraction level and metric for specific problems. To illustrate these points, we first study the use of Quad-Trees to characterize swarms, and then compare different methods using the metrics efficacy and efficiency. The goal of this work is to create an architecture and processes that will enable a self-aware system to conduct these types of experiments, and use these methods and metrics for analyzing the appropriateness and the impact of abstraction levels in order to improve its own performance.