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Context-Aware Decision Support in Dynamic Environments: Theoretical and Technological Foundations

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Simulation and Modeling Methodologies, Technologies and Applications

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 319))

Abstract

The paper addresses the issue of context-aware operational decision support in dynamic environments. The context model specifies conceptual knowledge describing the situation and problems to be solved in this situation. This model comprises knowledge captured from an application ontology, which is formalized by a set of constraints. The context aware decision support system (DSS) developed within the research has a service-oriented architecture. The Web-services constituting the architecture provide the DSS with the contextualized information from information resources, solve problems specified in the context, and participate in decision making. A decision making model overstepping the limits of the three-phase Simon’s model is offered. The paper proposes a set of technologies that can be used to implement the ideas behind the research. An application of these ideas is illustrated by an example of usage of the developed DSS for planning fire response actions.

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Acknowledgments

The present research was partly supported by the projects funded through grants 12–07–00298, 13–07–00336, 13–07–12095, 13–07–13159, 14–07–00345, 14–07–00427 (the Russian Foundation for Basic Research), the Project 213 (the research program “Information, control, and intelligent technologies & systems” of the Russian Academy of Sciences (RAS)), the Project 2.2 (the Nano- & Information Technologies Branch of RAS), and grant 074–U01 (the Government of the Russian Federation).

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Smirnov, A., Levashova, T., Shilov, N., Kashevnik, A. (2015). Context-Aware Decision Support in Dynamic Environments: Theoretical and Technological Foundations. In: Obaidat, M., Koziel, S., Kacprzyk, J., Leifsson, L., Ă–ren, T. (eds) Simulation and Modeling Methodologies, Technologies and Applications. Advances in Intelligent Systems and Computing, vol 319. Springer, Cham. https://doi.org/10.1007/978-3-319-11457-6_1

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  • DOI: https://doi.org/10.1007/978-3-319-11457-6_1

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