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A Context-Aware Multi-Agent System as a Middleware for Ambient Intelligence

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Abstract

There is currently a lot of work in Ambient Intelligence—or AmI—reporting on specific scenarios, or on implementations of particular cases. In the same time, there is a common agreement of the fact that AmI applications should be pervasive, covering a large number of devices, assisting a large number of people, and serving a large number of purposes. In an attempt to achieve scalable scenarios and implementations, we have focused our research on the development of a generic middleware layer for the context-aware transfer and exchange of information between devices. This paper presents a model for a such middleware, based on software agents, in which context-awareness is implemented both in the agent’s representation of context information, and in the logical topology of the agent system. The model is oriented towards decentralization of the system and relies mostly on local behavior. The paper also reports on several proof-of-concept applications that have been developed and tested using the proposed model, proving thus the validity of the approach.

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Notes

  1. We will mark with “ P ” graphs and elements that contain ? nodes, regular expressions, and other generic features.

  2. There may be multiple matches between the same pattern and the same graph.

  3. The Ao Dai project has been implemented in collaboration with Thi Thuy Nga Nguyen and Diego Salomone-Bruno, under the supervision of prof. Amal El Fallah Seghrouchni.

  4. Workshop held in collaboration by the National Institute of Informatics in Tokyo and the Laboratory of Computer Science of University Paris 6. Details at http://www-desir.lip6.fr/~herpsonc/5workshopNii/program.htm.

  5. The realization of the platform has been a collaborative effort of Andrei Olaru, Thi Thuy Nga Nguyen and Marius-Tudor Benea, under the supervision of prof. Amal El Fallah Seghrouchni and with the assistance of Cédric Herpson.

  6. Java Agent Development Framework http://jade.tilab.com/.

  7. http://www.android.com/

  8. These features have been developed by Marius Tudor Benea during his internship at LIP6.

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Acknowledgements

The authors would like to thank Cristian Gratie for the participation in the development of the AmIciTy platform; Thi Thuy Nga Nguyen and Diego Salomone Bruno for their participation in the development of the Ao Dai prototype; and Marius Tudor Benea and again Thi Thuy Nga Nguyen for their participation in the development of the Ao Dai platform, as well as to Cédric Herpson for his assistance and advise.

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Authors and Affiliations

  1. Department of Computer Science, University Politehnica of Bucharest, 313 Splaiul Independentei, 060042, Bucharest, Romania

    Andrei Olaru & Adina Magda Florea

  2. Laboratoire d’Informatique de Paris 6, University Pierre et Marie Curie, 4 Place Jussieu, 75005, Paris, France

    Amal El Fallah Seghrouchni

Authors
  1. Andrei Olaru
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  2. Adina Magda Florea
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  3. Amal El Fallah Seghrouchni
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Corresponding author

Correspondence to Andrei Olaru.

Additional information

This work has been supported by CNCSIS–UEFISCSU, project number PNII–IDEI 1315/2008.

Both Andrei Olaru and Adina Magda Florea are main authors of this paper.

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Olaru, A., Florea, A.M. & El Fallah Seghrouchni, A. A Context-Aware Multi-Agent System as a Middleware for Ambient Intelligence. Mobile Netw Appl 18, 429–443 (2013). https://doi.org/10.1007/s11036-012-0408-9

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