Malkomes, G, Lu, K, Hoffman, B et al. (3 more authors) (2017) Cooperative Set Function Optimization Without Communication or Coordination. In: Larson, K, Winikoff, M, Das, S and Durfee, E, (eds.) AAMAS '17 Proceedings of the 16th Conference on Autonomous Agents and MultiAgent Systems. AAMAS '17, 08-12 May 2017, Sao Paulo, Brazil. International Foundation for Autonomous Agents and Multiagent Systems , pp. 1109-1118.
Abstract
We introduce a new model for cooperative agents that seek to optimize a common goal without communication or coordination. Given a universe of elements V, a set of agents, and a set function f, we ask each agent i to select a subset Si ⊂ V such that the size of Si is constrained (i.e., |Si| < k). The goal is for the agents to cooperatively choose the sets Si to maximize the function evaluated at the union of these sets, ∪iSi; we seek max f(∪iSi). We assume the agents can neither communicate nor coordinate how they choose their sets. This model arises naturally in many real-world settings such as swarms of surveillance robots and colonies of foraging insects. Even for simple classes of set functions, there are strong lower bounds on the achievable performance of coordinating deterministic agents. We show, surprisingly, that for the fundamental class of submodular set functions, there exists a near-optimal distributed algorithm for this problem that does not require communication. We demonstrate that our algorithm performs nearly as well as recently published algorithms that allow full coordination.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2017, International Foundation for Autonomous Agents and Multiagent Systems (www.ifaamas.org). All rights reserved. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in AAMAS '17 Proceedings of the 16th Conference on Autonomous Agents and MultiAgent Systems. Uploaded in accordance with the publisher's self-archiving policy. |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Mathematics (Leeds) > Statistics (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 27 Jan 2017 12:48 |
Last Modified: | 22 May 2018 23:26 |
Published Version: | https://dl.acm.org/citation.cfm?id=3091281 |
Status: | Published |
Publisher: | International Foundation for Autonomous Agents and Multiagent Systems |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:111241 |