Abstract
Gaining a fundamental understanding of adjustable autonomy (AA) is critical if we are to deploy multi-agent systems in support of critical human activities. Indeed, our recent work with intelligent agents in the “Electric Elves” (E-Elves) system has convinced us that AA is a critical part of any human collaboration software. In the following, we first briefly describe E-Elves, then discuss AA issues in E-Elves.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Tom Mitchell, Rich Caruana, Dayne Freitag, John McDermott, and David Zabowski. Experience with a learning personal assistant. Communications of the ACM, 37(7):81–91, July 1994.
J. R. Quinlan. C4.5: Programs for machine learning. Morgan Kaufmann, San Mateo, CA, 1993.
M. Tambe. Towards flexible teamwork. Journal of Artificial Intelligence Research (JAIR), 7:83–124, 1997.
Milind Tambe, David V. Pynadath, Nicolas Chauvat, Abhimanyu Das, and Gal A. Kaminka. Adaptive agent integration architectures for heterogeneous team members. In Proceedings of the International Conference on MultiAgent Systems, pages 301–308, 2000.
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
Tambe, M., Pynadath, D., Scerri, P. (2001). Adjustable Autonomy: A Response. In: Castelfranchi, C., Lespérance, Y. (eds) Intelligent Agents VII Agent Theories Architectures and Languages. ATAL 2000. Lecture Notes in Computer Science(), vol 1986. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44631-1_29
Download citation
DOI: https://doi.org/10.1007/3-540-44631-1_29
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-42422-2
Online ISBN: 978-3-540-44631-6
eBook Packages: Springer Book Archive