By Peter R. Lewis, Marco Platzner, Bernhard Rinner, Jim Tørresen, Xin Yao
Taking notion from self-awareness in people, this booklet introduces the hot concept of computational self-awareness as a primary idea for designing and working computing structures. the elemental skill of such self-aware computing platforms is to gather information regarding their nation and development, studying and conserving types containing wisdom that permits them to cause approximately their behaviour. Self-aware computing platforms can have the facility to utilise this data to successfully and autonomously adapt and clarify their behaviour, in altering conditions.
This publication addresses those primary ideas from an engineering standpoint, aiming at constructing primitives for construction platforms and purposes. will probably be of worth to researchers, pros and graduate scholars in machine technological know-how and engineering.
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Additional info for Self-aware Computing Systems: An Engineering Approach
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In this chapter, we take inspiration from human self-awareness to develop new notions of computational self-awareness and self-expression. We translate concepts from psychology to the domain of computing, introducing key ideas in self-aware computing. In doing so, this chapter therefore paves the way for subsequent work in this book. ” Informally, we might typically consider that humans build up knowledge, or become aware of things, by perceiving the world around them. We observe interactions, listen to other people, watch television, read books, and, particularly in early life, learn through play.
While the book includes some of the research results, it also, and more importantly, serves the purpose of stimulating further research into the field of self-aware and self-expressive computing systems. Part I Concepts and Fundamentals Part I motivates the concepts of self-awareness and self-expression for engineering computing systems by looking into other disciplines and related concepts. It introduces a reference architecture for describing and engineering computational self-awareness and self-expression in computing systems.
Many techniques and algorithms are needed to support and implement selfawareness and self-expression at different levels. , learning while the system is running. Online learning algorithms are one of the key ingredients employed in self-aware and self-expressive systems. These algorithms try to make the most appropriate (tradeoff) decision among several conflicting goals in a dynamic and uncertain environment, including what information to acquire, which level of abstraction to use to capture and model such information, and what resources to use for such information acquiring and modelling so as to maximise the expected performance gain and minimise the resource usage, etc.