Title
Artificial Immunology for Collective Adaptive Systems Design and Implementation.
Abstract
Distributed autonomous systems consisting of large numbers of components with no central control point need to be able to dynamically adapt their control mechanisms to deal with an unpredictable and changing environment. Existing frameworks for engineering self-adaptive systems fail to account for the need to incorporate self-expression—that is, the capability of a system to dynamically adapt its coordination pattern during runtime. Although the benefits of incorporating self-expression are well known, currently there is no principled means of enabling this during system design. We propose a conceptual framework for principled design of systems that exhibit self-expression, based on inspiration from the natural immune system. The framework is described as a set of design principles and customizable algorithms and then is instantiated in three case studies, including two from robotics and one from artificial chemistry. We show that it enables self-expression in each case, resulting in systems that are able to adapt their choice of coordination pattern during runtime to optimize functional and nonfunctional goals, as well as to discover novel patterns and architectures.
Year
DOI
Venue
2016
10.1145/2897372
TAAS
Keywords
Field
DocType
Design,Experimentation,Autonomic computing,artificial immune system,framework
Autonomic computing,Artificial immune system,Artificial chemistry,Computer science,Systems design,Software,Autonomous system (Internet),Artificial intelligence,Conceptual framework,Robotics,Distributed computing
Journal
Volume
Issue
ISSN
11
2
1556-4665
Citations 
PageRank 
References 
4
0.44
30
Authors
3
Name
Order
Citations
PageRank
Nicola Capodieci18216.13
Emma Hart29718.02
Giacomo Cabri31018106.91