Skip to main content

Human-Centered Planning for Adaptive User Situation in Ambient Intelligence Environment

  • Conference paper

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7047))

Abstract

The new intelligence system named Ambient Intelligence (AmI) is now in the limelight. In this AmI environment, when multiple people in various situations cooperate mutually, they need to to be supported simultaneously and effectively. Furthermore, peoples’ context and activities change continuously, so it is also necessary to achieve dynamic correspondence between people. Therefore, a planning agent has been developed to enable context-aware service composition. The planning agent creates plans dynamically to support multiple people in different environments. In the experiment, the dish event scenario was adopted and the planning agent allotted multiple people ingredient collection tasks.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Augusto, J.C.: Ambient intelligence: the confluence of ubiquitous/pervasive computing and artificial intelligence. In: Schuster, A. (ed.) Intelligent Computing Everywhere, pp. 213–234 (2007)

    Google Scholar 

  2. Augusto, J.C., Nugent, C.D.: The use of temporal reasoning and management of complex events in smart homes. In: 16th European Conference of Artificial Intelligence (ECAI 2004), pp. 778–782 (2004)

    Google Scholar 

  3. Bajo, J., Tapia, D.I., Rodr-iguez, S., Corchado, J.M.: Planning agent for health care: ambient intelligence in practice. In: Encyclopedia of Artificial Intelligence, pp. 1316–1322 (2008)

    Google Scholar 

  4. Bikakis, A., Antoniou, G.: Defeasible contextual reasoning with arguments in ambient intelligence. IEEE Transactions on Knowledge and Data Engineering 22(11), 1492–1506 (2010)

    Article  Google Scholar 

  5. Ester, M., Kriegel, H.P., Sander, J., Xu, X.: A density-based algorithm for discovering clusters in large spatial databases with noise. In: 2nd International Conference on Knowledge Discovery and Data Mining (KDD 1996), pp. 226–231 (1996)

    Google Scholar 

  6. Hattori, M., Cho, K., Ohsuga, A., Isshiki, M., Honiden, S.: Context-aware agent platform in ubiquitous environments and its verification tests. In: IEEE International Conference on Pervasive Computing and Communications (PerCom 2003), pp. 547–552 (2003)

    Google Scholar 

  7. Jürgen, B., Vlad, C., Marc, L., Friedemann, M., Michael, R.: Social, economic and ethical implications of ambient intelligence and ubiquitous computing. In: Weber, W., Rabaey, J., Aarts, E. (eds.) Ambient Intelligence, pp. 5–29 (2005)

    Google Scholar 

  8. Mark, W.: The computer for the 21st century. ACM SIGMOBILE Mobile Computing and Communications Review 3(3) (1999)

    Google Scholar 

  9. Ohsuga, A., Nagai, Y., Irie, Y., Hattori, M., Honiden, S.: PLANGENT: An approach to making mobile agents intelligent. IEEE Internet Computing 1(4), 50–57 (1997)

    Article  Google Scholar 

  10. Patkos, T., Bikakis, A., Antoniou, G., Papadopouli, M., Plexousakis, D.: Distributed AI for Ambient Intelligence: Issues and Approaches. In: Schiele, B., Dey, A.K., Gellersen, H., de Ruyter, B., Tscheligi, M., Wichert, R., Aarts, E., Buchmann, A. (eds.) AmI 2007. LNCS, vol. 4794, pp. 159–176. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  11. Pei, J., Han, J., Mortazavi-Asl, B., Pinto, H., Chen, Q., Dayal, U., Hsu, M.-C.: Prefix-span: mining sequential patterns efficiently by prefix-projected pattern growth. In: 17th International Conference on Data Engineering (ICDE 2001), pp. 215–224 (2001)

    Google Scholar 

  12. Ramos, C., Augusto, J.C., Shapiro, D.: Ambient intelligence - the next step for artificial intelligence. IEEE Intelligent Systems 23(2), 15–18 (2008)

    Article  Google Scholar 

  13. Xuemei, L., Gang, X., Li, L.: RFID based smart home architecture for improving lives. In: Proceedings of the 2nd International Conference on Anti-Counterfeiting, Security, and Identification (ASID 2008), pp. 440–443 (2008)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2011 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Sando, M., Hishiyama, R. (2011). Human-Centered Planning for Adaptive User Situation in Ambient Intelligence Environment. In: Kinny, D., Hsu, J.Yj., Governatori, G., Ghose, A.K. (eds) Agents in Principle, Agents in Practice. PRIMA 2011. Lecture Notes in Computer Science(), vol 7047. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25044-6_42

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-25044-6_42

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-25043-9

  • Online ISBN: 978-3-642-25044-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics