Skip to main content

Multi-agent Meeting Scheduling Using Mobile Context

  • Conference paper

Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST,volume 35)

Abstract

Despite the use of newer and more powerful calendar and collaboration tools, the task of scheduling and rescheduling meetings is very time consuming for busy professionals, especially for highly mobile people. Research projects and commercial calendar products have worked since the early 1990s on implementing intelligent meeting organizers to automate meeting scheduling. However, automated schedulers have not been widely accepted or used by professionals around the world. Our research shows that the task of organizing meeting can be improved by reducing the scheduling workload and making meeting logistics more efficient. For example, new tools can decide meeting venues and dynamically handle exceptions, such as one participant not being able to arrive at the meeting location on time. In this paper, we discuss a solution to effectively employ the mobile user’s context in making more intelligent decisions on behalf of the user. Business Meeting Organizer (BMO) is a multi-agent meeting scheduling system, designed to automate time and venue decisions and to handle exceptions. Rather than using a traditional multi-user calendar-based scheduler, BMO has representatives (“software secretaries” implemented as software agents) for each user to negotiate a best time for a particular meeting, taking into account availability, context and preferences. Several technologies are used by BMO to provide secure and intelligent meeting scheduling functionality. By using agent technology, BMO keeps private calendar information invisible to other meeting participants and allows diverse intelligent negotiation and scheduling policies to be employed. Through the use of a rules engine, BMO can consider meeting participants’ personal preferences as to when to schedule the meeting. By means of mobile devices, BMO can get the user’s context information, such as the user’s physical location, which may be helpful in deciding the meeting venue and handling other meeting issues. In this paper, we discuss a solution to effectively employ the user’s mobile context information in making more intelligent decisions on behalf of the user.

Keywords

  • context-aware
  • intelligent meeting scheduling
  • multi-agent system

This is a preview of subscription content, access via your institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • DOI: 10.1007/978-3-642-12607-9_15
  • Chapter length: 13 pages
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
eBook
USD   109.00
Price excludes VAT (USA)
  • ISBN: 978-3-642-12607-9
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Softcover Book
USD   139.00
Price excludes VAT (USA)

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Maes, P.: Agents that reduce work and information overload. Communications of the ACM 37(7), 30–40 (1994)

    CrossRef  Google Scholar 

  2. Haynes, T., Sen, S., Arora, N., Nadela, R.: An automated meeting scheduling system that utilizes user preferences. In: Proceedings of the First International Conference on Autonomous Agents (1997)

    Google Scholar 

  3. Lin, J.H., Wu, J., Lai, S.L.: A Multi-agent meeting scheduler that satisfies soft constraints. In: Proceedings of the Second International Conference on Multiagent Systems (1997)

    Google Scholar 

  4. Griss, M., Letsinger, R., Cowan, D., Vanhilst, M., Kessler, R.: CoolAgent: Intelligent Digital Assistants for Mobile, Professionals – Phase 1 Retrospective, HPL Technical Report (November 2001)

    Google Scholar 

  5. Sen, S., Durfee, E.H.: On the design of an adaptive meeting scheduler. In: Proceedings of the Tenth Conference on Artificial Intelligence for Applications (March 1994)

    Google Scholar 

  6. Crawford, E., Veloso, M.: Opportunities for learning in multi-agent meeting scheduling. In: Proceedings of the AAAI 2004 Symposium on Artificial Multiagent Learning, Washington, DC (2004)

    Google Scholar 

  7. Chen, H.: An intelligent broker architecture for context aware systems (2002)

    Google Scholar 

  8. Scheible, J., Tuulos, V.: Mobile Python: Rapid Prototyping of Applications on the Mobile Platform. Wiley, Chichester (2007), ISBN: 978-0-470-51505-1

    Google Scholar 

  9. Bellifemine, F.L., Caire, G., Greenwood, D.: Developing Multi-Agent Systems with JADE. Wiley, Chichester (2009), ISBN: 978-0-470-05840-4

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and Permissions

Copyright information

© 2010 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering

About this paper

Cite this paper

Yang, K., Pattan, N., Rivera, A., Griss, M. (2010). Multi-agent Meeting Scheduling Using Mobile Context. In: Phan, T., Montanari, R., Zerfos, P. (eds) Mobile Computing, Applications, and Services. MobiCASE 2009. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 35. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12607-9_15

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-12607-9_15

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-12606-2

  • Online ISBN: 978-3-642-12607-9

  • eBook Packages: Computer ScienceComputer Science (R0)