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6.2.1 Complexity Types: From Science to Systems Engineering
Author(s) -
Sheard Sarah A.,
Mostashari Ali
Publication year - 2011
Publication title -
incose international symposium
Language(s) - English
Resource type - Journals
ISSN - 2334-5837
DOI - 10.1002/j.2334-5837.2011.tb01235.x
Subject(s) - computer science , cognitive complexity , complexity management , system of systems , complex system , work (physics) , complexity science , data science , systems engineering , software engineering , management science , cognition , artificial intelligence , systems design , engineering , mechanical engineering , psychology , marketing , neuroscience , business
How to measure complexity for systems engineering is currently receiving great attention, including such efforts as DARPA's META program. However, complexity is a highly varying concept with many different views. This paper discusses some of those varieties of meaning, types of complexities, and entities which may be measured for complexity (qualitatively or quantitatively). First discussed are attributes that make a system complex and difficulties in dealing with the system because of the complexity (i.e. complexity causes and effects). Next types of complexity are reviewed from previous work. Finally those types of complexity are applied to four types of systems engineering entity: a project building a technological system, that system itself, the environment into which the system will be inserted, and the cognitive load on humans involved in the system. Ongoing and future work is also described.