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A scenario-based approach to multi-agent optimization with distributed information

Abstract:

In this paper, we consider optimization problems involving multiple agents. Each agent introduces its own constraints on the optimization vector, and the constraints of all agents depend on a common source of uncertainty. We suppose that uncertainty is known locally to each agent through a private set of data (multi-agent scenarios), and that each agent enforces its scenario-based constraints to the solution of the multi-agent optimization problem. Our goal is to assess the feasibility proper...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1016/j.ifacol.2020.12.034

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Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author
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Name:
Engineering and Physical Sciences Research Council
Grant:
EP/P03277X/1
Publisher:
Elsevier
Journal:
IFAC Papers Online More from this journal
Volume:
53
Issue:
2
Pages:
20-25
Publication date:
2021-04-14
Acceptance date:
2020-03-09
Event title:
21st IFAC World Congress
Event location:
Berlin, Germany
Event website:
https://www.ifac2020.org/
Event start date:
2020-07-12
Event end date:
2020-07-17
DOI:
ISSN:
1474-6670
Language:
English
Keywords:
Pubs id:
1091881
Local pid:
pubs:1091881
Deposit date:
2020-03-09

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