Performance-Aware Self-Configurable Multi-Agent Networks: A Distributed Submodular Approach for Simultaneous Coordination and Network Design
We introduce the first, to our knowledge, rigorous approach that enables multi-agent networks to self-configure their communication topology to balance the trade-off between scalability and optimality during multi-agent planning. We are motivated by the future of ubiquitous collaborative autonomy wh...
Gespeichert in:
| Veröffentlicht in: | Proceedings of the IEEE Conference on Decision & Control S. 5393 - 5400 |
|---|---|
| Hauptverfasser: | , |
| Format: | Tagungsbericht |
| Sprache: | Englisch |
| Veröffentlicht: |
IEEE
16.12.2024
|
| Schlagworte: | |
| ISSN: | 2576-2370 |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| Abstract | We introduce the first, to our knowledge, rigorous approach that enables multi-agent networks to self-configure their communication topology to balance the trade-off between scalability and optimality during multi-agent planning. We are motivated by the future of ubiquitous collaborative autonomy where numerous distributed agents will be coordinating via agent-to-agent communication to execute complex tasks such as traffic monitoring, event detection, and environmental exploration. But the explosion of information in such large-scale networks currently curtails their deployment due to impractical decision times induced by the computational and communication requirements of the existing near-optimal coordination algorithms. To overcome this challenge, we present the AlterNAting COordination and Network-Design Algorithm (Anaconda), a scalable algorithm that also enjoys near-optimality guarantees. Subject to the agents' bandwidth constraints, Anaconda enables the agents to optimize their local communication neighborhoods such that the action-coordination approximation performance of the network is maximized. Compared to the state of the art, Anaconda is an anytime self-configurable algorithm that quantifies its suboptimality guarantee for any type of network, from fully disconnected to fully centralized, and that, for sparse networks, is one order faster in terms of decision speed. To develop the algorithm, we quantify the suboptimality cost due to decentralization, i.e., due to communication-minimal distributed coordination. We also employ tools inspired by the literature on multi-armed bandits and submodular maximization subject to cardinality constraints. We demonstrate Anaconda in simulated scenarios of area monitoring and compare it with a state-of-the-art algorithm. |
|---|---|
| AbstractList | We introduce the first, to our knowledge, rigorous approach that enables multi-agent networks to self-configure their communication topology to balance the trade-off between scalability and optimality during multi-agent planning. We are motivated by the future of ubiquitous collaborative autonomy where numerous distributed agents will be coordinating via agent-to-agent communication to execute complex tasks such as traffic monitoring, event detection, and environmental exploration. But the explosion of information in such large-scale networks currently curtails their deployment due to impractical decision times induced by the computational and communication requirements of the existing near-optimal coordination algorithms. To overcome this challenge, we present the AlterNAting COordination and Network-Design Algorithm (Anaconda), a scalable algorithm that also enjoys near-optimality guarantees. Subject to the agents' bandwidth constraints, Anaconda enables the agents to optimize their local communication neighborhoods such that the action-coordination approximation performance of the network is maximized. Compared to the state of the art, Anaconda is an anytime self-configurable algorithm that quantifies its suboptimality guarantee for any type of network, from fully disconnected to fully centralized, and that, for sparse networks, is one order faster in terms of decision speed. To develop the algorithm, we quantify the suboptimality cost due to decentralization, i.e., due to communication-minimal distributed coordination. We also employ tools inspired by the literature on multi-armed bandits and submodular maximization subject to cardinality constraints. We demonstrate Anaconda in simulated scenarios of area monitoring and compare it with a state-of-the-art algorithm. |
| Author | Xu, Zirui Tzoumas, Vasileios |
| Author_xml | – sequence: 1 givenname: Zirui surname: Xu fullname: Xu, Zirui email: ziruixu@umich.edu – sequence: 2 givenname: Vasileios surname: Tzoumas fullname: Tzoumas, Vasileios email: vtzoumas@umich.edu organization: University of Michigan,Department of Aerospace Engineering,Ann Arbor,MI,USA,48109 |
| BookMark | eNo1kN1KwzAcxaMouM29gUheoDNpljTxrnR-wfyA6fVImn9mtE1G2jJ8Bx_agnrzO1fnB-dM0UmIARC6pGRBKVFX1ariosiXi5yMoERKIYv8CM1VoSTjhFHBmDpGk5wXIstZQc7QtOs-CGFKLdkEfb9AcjG1OtSQlQedAG-gcVkVg_O7IWnTAH4cmt5n5Q5Cj5-gP8T02V3jEq981ydvhh4s3gymjXZodMLlfp-irt_xKMYb345tHSAOHa5iTNYH3fsYsA7234ZX0PldOEenTjcdzP9yht5ub16r-2z9fPdQlevM00L0mVTcEsm0tmCAm2XtnLWkkNLUtWCF0dzxWipFwNlxZz0CaG2FoE4Yzg2boYtfrweA7T75Vqev7f977AeIxWo7 |
| ContentType | Conference Proceeding |
| DBID | 6IE 6IH CBEJK RIE RIO |
| DOI | 10.1109/CDC56724.2024.10886872 |
| DatabaseName | IEEE Electronic Library (IEL) Conference Proceedings IEEE Proceedings Order Plan (POP) 1998-present by volume IEEE Xplore All Conference Proceedings IEEE Electronic Library (IEL) IEEE Proceedings Order Plans (POP) 1998-present |
| DatabaseTitleList | |
| Database_xml | – sequence: 1 dbid: RIE name: IEEE Electronic Library (IEL) url: https://ieeexplore.ieee.org/ sourceTypes: Publisher |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Engineering |
| EISBN | 9798350316339 |
| EISSN | 2576-2370 |
| EndPage | 5400 |
| ExternalDocumentID | 10886872 |
| Genre | orig-research |
| GroupedDBID | 6IE 6IH 6IL 6IN AAWTH ABLEC ACGFS ADZIZ ALMA_UNASSIGNED_HOLDINGS BEFXN BFFAM BGNUA BKEBE BPEOZ CBEJK CHZPO IEGSK IJVOP M43 OCL RIE RIL RIO |
| ID | FETCH-LOGICAL-i176t-895d083aadebe5b4cffdd0788bcc637ba5f5c8990efd039cd03e1cd661f6b55b3 |
| IEDL.DBID | RIE |
| ISICitedReferencesCount | 1 |
| ISICitedReferencesURI | http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=001445827204089&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| IngestDate | Wed Aug 27 01:48:44 EDT 2025 |
| IsPeerReviewed | false |
| IsScholarly | false |
| Language | English |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-i176t-895d083aadebe5b4cffdd0788bcc637ba5f5c8990efd039cd03e1cd661f6b55b3 |
| PageCount | 8 |
| ParticipantIDs | ieee_primary_10886872 |
| PublicationCentury | 2000 |
| PublicationDate | 2024-Dec.-16 |
| PublicationDateYYYYMMDD | 2024-12-16 |
| PublicationDate_xml | – month: 12 year: 2024 text: 2024-Dec.-16 day: 16 |
| PublicationDecade | 2020 |
| PublicationTitle | Proceedings of the IEEE Conference on Decision & Control |
| PublicationTitleAbbrev | CDC |
| PublicationYear | 2024 |
| Publisher | IEEE |
| Publisher_xml | – name: IEEE |
| SSID | ssj0039943 |
| Score | 1.9077854 |
| Snippet | We introduce the first, to our knowledge, rigorous approach that enables multi-agent networks to self-configure their communication topology to balance the... |
| SourceID | ieee |
| SourceType | Publisher |
| StartPage | 5393 |
| SubjectTerms | Approximation algorithms Costs Event detection Explosions Knowledge engineering Monitoring Network topology Planning Scalability Topology |
| Title | Performance-Aware Self-Configurable Multi-Agent Networks: A Distributed Submodular Approach for Simultaneous Coordination and Network Design |
| URI | https://ieeexplore.ieee.org/document/10886872 |
| WOSCitedRecordID | wos001445827204089&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1LT4NAEN5o40Evvmp8Zw9eV6Gwu-CNUBsPpmlSTXprlt1ZQ6JgaNE_4Y92FqjVgwcvG0LCQGZgZnb4vhlCroIIH883inmhr1hoecZiz2jGZWZFLGPMuJvu-g9yPI5ms3jSkdUbLgwANOAzuHaHzb98U-ralcrwC48iEUn0uJtSipastXK7GGjDoKMA-158kw5TLuTAlU1wWV35a4ZKE0JGu_-8-R7pr8l4dPIdZvbJBhQHZOdHH8FD8jlZw_9Z8qEqoFN4scxJyJ_rytGjaEO1ZYmjUtFxC_5e3NKEDl3rXDf1CgxFN_JaGodMpUnXbJyiYDrNHfBQFVDWC5qWuGHN2yoiVYVZSaPDBg3SJ0-ju8f0nnVjFljuS7FkUcwNJmJKGTQoz0JtrTGYOUSZ1iKQmeKWa9yWeWANqlnjAr42GNityDjPgiPSK8oCjgnVYPGdsCYwMgitDygad2RSKyO9QQz2hPSdYudvbSeN-Uqnp3-cPyPbznwOPuKLc9JbVjVckC39vswX1WVj_y9EhLZ0 |
| linkProvider | IEEE |
| linkToHtml | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1LT4NAEN6YaqJefNX4dg9eV6GwLHgj1KbGSpq0Jr01yz4MiYKhRf-EP9pZHlYPHrxsCAkDmV1mZme_bwahK8eHz7MlJ5Zrc-JqmpDAkoJQlmgvYAFE3FV1_RGLY382C8YNWb3iwiilKvCZujaX1Vm-zEVpUmXwh_u-5zOwuOvUdXtWTddqDS-4WtdpSMC2FdxE_Yh6rGcSJzC0z_7qolI5kcHOP1-_i7orOh4efzuaPbSmsn20_aOS4AH6HK8IACT84IXCE_WiiZGQPpeFIUjhimxLQkOmwnEN_17c4hD3TfFc0_dKSQyG5DWXBpuKw6bcOAbBeJIa6CHPVF4ucJTDljWt84iYZ7KVhvsVHqSLngZ302hImkYLJLWZtyR-QCWEYpxLmFKauEJrKSF28BMhPIclnGoqYGNmKS1BzQIGZQsJrl17CaWJc4g6WZ6pI4SF0rAqtHQkc1xtKxANezImuGRWL1D6GHWNYudvdS2NeavTkz_uX6LN4fRxNB_dxw-naMtMpQGT2N4Z6iyLUp2jDfG-TBfFRbUWvgDnC7m7 |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Abook&rft.genre=proceeding&rft.title=Proceedings+of+the+IEEE+Conference+on+Decision+%26+Control&rft.atitle=Performance-Aware+Self-Configurable+Multi-Agent+Networks%3A+A+Distributed+Submodular+Approach+for+Simultaneous+Coordination+and+Network+Design&rft.au=Xu%2C+Zirui&rft.au=Tzoumas%2C+Vasileios&rft.date=2024-12-16&rft.pub=IEEE&rft.eissn=2576-2370&rft.spage=5393&rft.epage=5400&rft_id=info:doi/10.1109%2FCDC56724.2024.10886872&rft.externalDocID=10886872 |