Towards systems that dynamically change and evaluate abstractions

Ada Diaconescu; David King; Kirstie Bellman; Christopher Landauer; Phyllis Nelson

doi:10.29007/qtpl

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Towards systems that dynamically change and evaluate abstractions

9 pages•Published: July 12, 2024

Ada Diaconescu, David King, Kirstie Bellman, Christopher Landauer and Phyllis Nelson

Abstract

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.

Keyphrases: abstraction levels, Self-Aware Systems, swarm tracking

In: Kenneth Baclawski, Michael Kozak, Kirstie Bellman, Giuseppe D'Aniello, Alicia Ruvinsky and Candida Da Silva Ferreira Barreto (editors). Proceedings of Conference on Cognitive and Computational Aspects of Situation Management 2023, vol 102, pages 154--162

Links:	https://easychair.org/publications/paper/TJWB
	https://doi.org/10.29007/qtpl

BibTeX entry

@inproceedings{CogSIMA2023:Towards_systems_that_dynamically,
  author    = {Ada Diaconescu and David King and Kirstie Bellman and Christopher Landauer and Phyllis Nelson},
  title     = {Towards systems that dynamically change and evaluate abstractions},
  booktitle = {Proceedings of Conference on Cognitive and Computational Aspects of Situation Management 2023},
  editor    = {Kenneth Baclawski and Michael Kozak and Kirstie Bellman and Giuseppe D'Aniello and Alicia Ruvinsky and Candida Da Silva Ferreira Barreto},
  series    = {EPiC Series in Computing},
  volume    = {102},
  pages     = {154--162},
  year      = {2024},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2398-7340},
  url       = {https://easychair.org/publications/paper/TJWB},
  doi       = {10.29007/qtpl}}

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