Abstract
Offering an individually tailored service to passengers while maintaining a high transportation capacity of an elevator group is an upcoming challenge in the elevator business, which cannot be met by software methods traditionally used in this industry. AI planning offers a novel solution to these control problems: (1) by synthesizing the optimal control for any situation occurring in a building based on fast search algorithms, (2) by implementing a domain model, which allows to easily add new features to the control software. By embedding the planner into a multi-agent system, real-time interleaved planning and execution is implemented and results in a highperforming, self-adaptive, and modular control software.
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Reference
J. Koehler and K. Schuster. Elevator control as a planning problem. In S. Chien, S. Kambhampati, and C. Knoblock, editors, Proceedings of the 5th International Conference on Artificial Intelligence Planning and Scheduling, pages 331–338. AAAI Press, Menlo Park, 2000.
Jana Koehler. Von der Theorie zur Praxis: Verkehrsplanung für Hochleistungsaufz üge. Künstliche Intelligenz, 2, 2001.
B. Seckinger. Synthese von Aufzugssteuerungen mit Hilfe von Constraintbasierten Suchverfahren. Master’s thesis, Albert-Ludwigs-Universität Freiburg, 1999.
Bernhard Seckinger and Jana Koehler. Online-Synthese von Aufzugssteuerungen als Planungsproblem. In 13. Workshop Planen und Konfigurieren,Interner Bericht des Instituts für Informatik der Universität Würzburg, pages 127–134, 1999.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2001 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Koehler, J. (2001). From Theory to Practice: AI Planning for High Performance Elevator Control. In: Baader, F., Brewka, G., Eiter, T. (eds) KI 2001: Advances in Artificial Intelligence. KI 2001. Lecture Notes in Computer Science(), vol 2174. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45422-5_33
Download citation
DOI: https://doi.org/10.1007/3-540-45422-5_33
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-42612-7
Online ISBN: 978-3-540-45422-9
eBook Packages: Springer Book Archive