Abstract
Chapter 5 has provided step-by-step guidelines on how to design selfaware and self-expressive systems, including several architectural patterns with different levels of self-awareness. Chapter 6 has explained important features in self-aware and self-expressive systems, including adaptivity, robustness, multiobjectivity and decentralisation. To allow such self-aware capabilities in each design pattern and enable those system features, this chapter introduces the common techniques that have been used and can be used in self-aware (SA) and selfexpressive (SE) systems, including online learning, nature-inspired learning and socially-inspired learning in collective systems. Online learning allows learning in real time and thus has great flexibility and adaptivity. Nature-inspired learning provides tools to optimise SA/SE systems that can be used to reduce system complexity and costs. Socially-inspired learning is inspired by common social behaviours to facilitate learning, particularly in multi-agent systems that are commonly seen in SA/SE systems. How these techniques contribute to SA/SE systems is explained through several case studies. Their potentials and limitations are widely discussed at different self-awareness levels.
| Original language | English |
|---|---|
| Title of host publication | Natural Computing Series |
| Publisher | Springer Verlag |
| Pages | 113-142 |
| Number of pages | 30 |
| DOIs | |
| Publication status | Published - 2016 |
Publication series
| Name | Natural Computing Series |
|---|---|
| ISSN (Print) | 1619-7127 |
Bibliographical note
Publisher Copyright:© Springer International Publishing Switzerland 2016.
ASJC Scopus subject areas
- Software
- Theoretical Computer Science