Pournaras, E orcid.org/0000-0003-3900-2057 (2021) How to Coordinate Decisions at Large Scale? A Hands-on Tutorial on Collective Learning for Smart Cities and beyond. In: 2021 IEEE International Conference on Autonomic Computing and Self-Organizing Systems Companion (ACSOS-C). 2021 IEEE International Conference on Autonomic Computing and Self-Organizing Systems Companion (ACSOS-C), 27 Sep - 01 Oct 2021, Washington, D.C, USA. IEEE , p. 319. ISBN 978-1-6654-4393-7
Abstract
This 1.5-hour tutorial will provide an introduction to the theory and practice of multi-agent collective learning for coordinating distributed decisions at large scale. You will develop the required skills to work with the EPOS software artifact to solve distributed optimization problems in Smart Cities. The tutorial will also promote collaborations within the ACSOS community. PhD students and more senior colleagues are particularly encouraged to participate. No programming experience is required. You are also encouraged to bring in your own multi-agent optimization problem to explore a potential solution using collective learning.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
Keywords: | collective learning, multi-agent system, combinatorial optimization, coordination, decision-making, Smart City |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds) |
Funding Information: | Funder Grant number Swiss National Science Foundation Not Known |
Depositing User: | Symplectic Publications |
Date Deposited: | 15 Feb 2022 15:46 |
Last Modified: | 15 Feb 2022 15:46 |
Status: | Published |
Publisher: | IEEE |
Identification Number: | 10.1109/ACSOS-C52956.2021.00084 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:183584 |