Metasynthesis: M-space, M-interaction, and M-computing for open complex giant systems

Document Type

Article

Publication Date

7-16-2009

Abstract

The studies of complex systems have been recognized as one of the greatest challenges for current and future science and technology. Open complex giant systems (OCGSs) are a family of specially complex systems with system complexities such as openness, human involvement, societal characteristic, and intelligence emergence. They greatly challenge multiple disciplines such as system sciences, system engineering, cognitive sciences, information systems, artificial intelligence, and computer sciences. As a result, traditional problem-solving methodologies can help deal with them but are far from a mature solution methodology. The theory of qualitative-to-quantitative metasynthesis has been proposed as a breakthrough and effective methodology for the understanding and problem solving of OCGSs. In this paper, we propose the concepts of M-Interaction, M-Space, and M-Computing which are three key components for studying OCGS and building problem-solving systems. M-Interaction forms the main problem-solving mechanism of qualitative-to-quantitative metasynthesis; M-Space is the OCGS problem-solving system embedded with M-Interactions, while M-Computing consists of engineering approaches to the analysis, design, and implementation of M-Space and M-Interaction. We discuss the theoretical framework, problem-solving process, social cognitive evolution, intelligence emergence, and pitfalls of certain types of cognitions in developing M-Space and M-Interaction from the perspectives of cognitive sciences and social cognitive interaction. These can help one understand complex systems and develop effective problem-solving methodologies. © 2009 IEEE.

Identifier

69649095536 (Scopus)

Publication Title

IEEE Transactions on Systems Man and Cybernetics Part A Systems and Humans

External Full Text Location

https://doi.org/10.1109/TSMCA.2009.2022414

ISSN

10834427

First Page

1007

Last Page

1021

Issue

5

Volume

39

Grant

DP0667060

Fund Ref

Australian Research Council

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