Variable-Delay Controllability
Name
variable-delay-controllability.pdf
Description
Accepted version
Size
1003.96 KB
Format
Adobe PDF
Checksum (MD5)
16d2a595d5cf071ece4ba668463ae5f7
Author(s)
Bhargava, Nikhil
Muise, Christian
Williams, Brian
Date Issued
July 2018
Journal
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence
Publisher
International Joint Conferences on Artificial Intelligence
Citation
Bhargava, Nikhil, Christian Muise and Brian Williams. “Variable-Delay Controllability.” In Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, Stockholm, Sweden, July 13-19, 2018, International Joint Conferences on Artificial Intelligence, pp. 4660-4666 © 2019 The Author(s)
Version
Author's final manuscript
Abstract
In temporal planning, agents must schedule a set of events satisfying a set of predetermined constraints. These scheduling problems become more difficult when the duration of certain actions are outside the agent's control. Delay controllability is the generalized notion of whether a schedule can be constructed in the face of uncertainty if the agent eventually learns when events occur. Our work introduces the substantially more complex setting of determining variable-delay controllability, where an agent learns about events after some unknown but bounded amount of time has passed. We provide an efficient O(n3) variable-delay controllability checker and show how to create an execution strategy for variable-delay controllability problems. To our knowledge, these essential capabilities are absent from existing controllability checking algorithms. We conclude by providing empirical evaluations of the quality of variable-delay controllability results as compared to approximations that use fixed delays to model the same problems.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.24963/IJCAI.2018/648
