Ant-Inspired Dynamic Task Allocation via Gossiping
Name
SSDL-sub.pdf
Description
Submitted version
Size
406.86 KB
Format
Unknown
Checksum (MD5)
285b9a0d7394a307d757ca74f0b843f6
Author(s)
Su, Hsin-Hao
Su, Lili
Dornhaus, Anna
Lynch, Nancy A.
Date Issued
2017
Publisher
Springer Nature
Citation
Su, Hsin-Hao, Su, Lili, Dornhaus, Anna and Lynch, Nancy. 2017. "Ant-Inspired Dynamic Task Allocation via Gossiping."
Version
Original manuscript
Abstract
© Springer International Publishing AG 2017. We study the distributed task allocation problem in multi-agent systems, where each agent selects a task in such a way that, collectively, they achieve a proper global task allocation. In this paper, inspired by specialization on division of labor in ant colonies, we propose several scalable and efficient algorithms to dynamically allocate the agents as the task demands change. The algorithms have their own pros and cons, with respect to (1) how fast they react to dynamic demands change, (2) how many agents need to switch tasks, (3) whether extra agents are needed, and (4) whether they are resilient to faults.
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/10.1007/978-3-319-69084-1_11
