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Categorical Representation of Decision-Making Process Guided by Performance in Enterprise Integration Systems

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Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing

Abstract

The research work presented in this paper is motivated by the need to build performance measurement and decision making process into the enterprise models, a need rooted in the current industrial trend toward developing complex integrated enterprises. In order to accomplish Enterprise Integration (EI) compliance with the imposed performance requirements we formalize the EI modeling and performance control in a single formal framework based on representational theory of measurement and category theory. Category theory is expressive enough to capture qualitative and quantitative knowledge about heterogeneous EI requirements, their interrelations and decision-making mechanism in one formal representation, where structure and reasoning are inextricably bound together.  Thus, category theory provides a computational mechanism whereby such knowledge can be applied to EI data and information structures to arrive at conclusions which are valid.

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Ormandjieva, O., Mikhnovsky, V., Klasa, S. (2009). Categorical Representation of Decision-Making Process Guided by Performance in Enterprise Integration Systems. In: Lee, R., Ishii, N. (eds) Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing. Studies in Computational Intelligence, vol 209. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01203-7_19

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  • DOI: https://doi.org/10.1007/978-3-642-01203-7_19

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-01202-0

  • Online ISBN: 978-3-642-01203-7

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