Title
Genetically modified software: realizing viable autonomic agency
Abstract
Inspired by the autonomic aspects of the human central nervous system, the vision of “autonomiccomputing” arrived with a fully-formed wish list of characteristics that such systems should exhibit, essentially those self-referential aspects required for effective self-management. Here, the authors contend that the biologically-inspired managerial cybernetics of Beer’s Viable System Model (VSM) provides significant conceptual guidance for the development of a general architecture for the operation and management of such complex, evolving, adaptive systems. Consequently, the VSM has been used as the basis of a theoretically-supported reference model that provides the "blueprint" for an extensible intelligent agent architecture. Of course, normal use of the VSM relies heavily on human agency to realize the adaptive capabilities required by the model. Therefore, artificially replicating such activities represents a significant challenge, however the authors show that some progress can be made using algorithmic hot swapping and in particular Holland’s Genetic Algorithms (GA’s) to generate, in specific circumstances, a repertoire of tailored responses to environmental change. The authors then speculate on the use of the associated Learning Classifier Systems (LCS) approach to allow the system to develop an adaptive environmental model of appropriate, optimized responses.
Year
DOI
Venue
2005
10.1007/11964995_16
WRAC
Keywords
Field
DocType
environmental change,human central nervous system,extensible intelligent agent architecture,normal use,theoretically-supported reference model,general architecture,human agency,viable autonomic agency,adaptive system,adaptive capability,adaptive environmental model,genetically modified software,autonomic computing,genetic algorithm,genetically modified,central nervous system,intelligent agent,reference model,profitability,viable system model
Hot swapping,Intelligent agent,Reference model,Software engineering,Adaptive system,Viable system model,Variety (cybernetics),Artificial intelligence,Engineering,Genetic algorithm,Cybernetics
Conference
Volume
ISSN
ISBN
3825
0302-9743
3-540-69265-7
Citations 
PageRank 
References 
1
0.37
3
Authors
3
Name
Order
Citations
PageRank
A. G. Laws191.40
A. Taleb-Bendiab238348.64
Stephen J. Wade3121.64