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Annual Conference on Artificial Intelligence

KI 1996: KI-96: Advances in Artificial Intelligence pp 85–97Cite as

Towards a totally distributed meeting scheduling system

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1137))

Abstract

Meeting scheduling is an everyday task which is iterative, time-consuming, and tedious. Furthermore, it is a naturally distributed task where all attendees try to schedule a common meeting (their group goal) taking into account their individual preferences (their individual goals). In this paper, we present our preliminary work towards this direction; we view meeting scheduling as a distributed task where each agent knows its user's preferences and calendar availability in order to act on behalf of its user. Our experiments investigate how the calendar and preference privacy affect the process efficiency and the meeting joint quality under different experimental scenarios. The results show that the group performance is more stable and constant when agents try to keep their calendar and preference information private. We believe that these parameters play a key role in the non-centralized meeting scheduling task, specially if we are interested in building truly autonomous and independent agents.

This research has been sponsored in part by CONACYT under their scholarship program and by ITESM Campus Monterrey under their PCP program. Most of this work has been conducted at The Robotics Institute in Carnegie Mellon University.

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Author information

Authors and Affiliations

  1. Center for Artificial Intelligence, ITESM, Sucursal de Correos “J”, 64849, Monterrey, N.L., México

    Leonardo Garrido-Luna

  2. The Robotics Institute, Carnegie Mellon University, 15213, Pittsburgh, PA, USA

    Katia Sycara

Authors
  1. Leonardo Garrido-Luna
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  2. Katia Sycara
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Editor information

Günther Görz Steffen Hölldobler

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© 1996 Springer-Verlag Berlin Heidelberg

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Garrido-Luna, L., Sycara, K. (1996). Towards a totally distributed meeting scheduling system. In: Görz, G., Hölldobler, S. (eds) KI-96: Advances in Artificial Intelligence. KI 1996. Lecture Notes in Computer Science, vol 1137. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-61708-6_50

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  • DOI: https://doi.org/10.1007/3-540-61708-6_50

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-61708-2

  • Online ISBN: 978-3-540-70669-4

  • eBook Packages: Springer Book Archive

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