Canonical failure modes of real-time control systems: insights from cognitive theory
Rodrick Wallace
International Journal of Systems Science, 2016, vol. 47, issue 6, 1280-1295
Abstract:
Newly developed necessary conditions statistical models from cognitive theory are applied to generalisation of the data-rate theorem for real-time control systems. Rather than graceful degradation under stress, automatons and man/machine cockpits appear prone to characteristic sudden failure under demanding fog-of-war conditions. Critical dysfunctions span a spectrum of phase transition analogues, ranging from a ground state of ‘all targets are enemies’ to more standard data-rate instabilities. Insidious pathologies also appear possible, akin to inattentional blindness consequent on overfocus on an expected pattern. Via no-free-lunch constraints, different equivalence classes of systems, having structure and function determined by ‘market pressures’, in a large sense, will be inherently unreliable under different but characteristic canonical stress landscapes, suggesting that deliberate induction of failure may often be relatively straightforward. Focusing on two recent military case histories, these results provide a caveat emptor against blind faith in the current path-dependent evolutionary trajectory of automation for critical real-time processes.
Date: 2016
References: View complete reference list from CitEc
Citations:
Downloads: (external link)
http://hdl.handle.net/10.1080/00207721.2014.923951 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:taf:tsysxx:v:47:y:2016:i:6:p:1280-1295
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/TSYS20
DOI: 10.1080/00207721.2014.923951
Access Statistics for this article
International Journal of Systems Science is currently edited by Visakan Kadirkamanathan
More articles in International Journal of Systems Science from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().