Common Techniques for Self-awareness and Self-expression

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 self-expression (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. Shuo Wang and Leandro Minku School of Computer Science, University of Birmingham, UK. e-mail: \{s.wang,l.l.minku\}@cs.bham.ac.uk Georg Nebehay Safety and Security Department, Austrian Institute of Technology, Austria. e-mail: [email protected] Lukas Esterle Institute of Networked and Embedded Systems, Alpen-Adria-University Klagenfurt, Austria. e-mail: [email protected] Kristian Nymoen Department of Musicology, University of Oslo, Norway. e-mail: [email protected]