de Lemos, Rogério (2024) Bio-inspired computing systems: handle with care, discard if need it. In: SEAMS '24: Proceedings of the 19th International Symposium on Software Engineering for Adaptive and Self-Managing Systems. . ACM ISBN 979-8-4007-0585-4. (doi:10.1145/3643915.3644096) (KAR id:106308)
PDF
Publisher pdf
Language: English
This work is licensed under a Creative Commons Attribution 4.0 International License.
|
|
Download this file (PDF/532kB) |
Preview |
Request a format suitable for use with assistive technology e.g. a screenreader | |
Official URL: https://doi.org/10.1145/3643915.3644096 |
Abstract
Nature has an excellent track record in solving problems, and while biological inspired approaches draw inspiration from nature, they should not emulate it blindly. What works for nature may not work for computer systems - bio-inspired computing comes to the rescue. In this position paper, we look into the problem of bio-inspired computing from two perspectives, that of models and algorithms. In the context of self-adaptive software systems, the challenge is to come up with approaches that are able to generate specific solutions on demand and during operational-time.
Item Type: | Conference or workshop item (Paper) |
---|---|
DOI/Identification number: | 10.1145/3643915.3644096 |
Uncontrolled keywords: | feedback control loop, models, reinforcement learning, Bio-inspired computing |
Subjects: | Q Science > QA Mathematics (inc Computing science) |
Divisions: | Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing |
SWORD Depositor: | JISC Publications Router |
Depositing User: | JISC Publications Router |
Date Deposited: | 19 Jun 2024 13:44 UTC |
Last Modified: | 28 Jun 2024 13:24 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/106308 (The current URI for this page, for reference purposes) |
- Link to SensusAccess
- Export to:
- RefWorks
- EPrints3 XML
- BibTeX
- CSV
- Depositors only (login required):