Task-Oriented Data Compression for Multi-Agent Communications Over Bit-Budgeted Channels

Various applications for inter-machine communications are on the rise. Whether it is for autonomous driving vehicles or the internet of everything, machines are more connected than ever to improve their performance in fulfilling a given task. While in traditional communications the goal has often be...

Celý popis

Uloženo v:

Podrobná bibliografie
Vydáno v:	IEEE open journal of the Communications Society Ročník 3; s. 1
Hlavní autoři:	Mostaani, Arsham, Vu, Thang X., Chatzinotas, Symeon, Ottersten, Bjorn
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York IEEE 2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	Algorithms Collaboration Communication channels communications for machine learning Communications systems Data compression data quantization machine learning for communications Multi-agent systems Multiagent systems Quantization (signal) semantic communications Semantics Task analysis Task-oriented communications semantic communications data quantization Task-oriented communications machine learning for communications communications for machine learning
ISSN:	2644-125X, 2644-125X
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!

Abstract	Various applications for inter-machine communications are on the rise. Whether it is for autonomous driving vehicles or the internet of everything, machines are more connected than ever to improve their performance in fulfilling a given task. While in traditional communications the goal has often been to reconstruct the underlying message, under the emerging task-oriented paradigm, the goal of communication is to enable the receiving end to make more informed decisions or more precise estimates/computations. Motivated by these recent developments, in this paper, we perform an indirect design of the communications in a multi-agent system (MAS) in which agents cooperate to maximize the averaged sum of discounted one-stage rewards of a collaborative task. Due to the bit-budgeted communications between the agents, each agent should efficiently represent its local observation and communicate an abstracted version of the observations to improve the collaborative task performance. We first show that this problem can be approximated as a form of data-quantization problem which we call task-oriented data compression (TODC). We then introduce the state-aggregation for information compression algorithm (SAIC) to solve the formulated TODC problem. It is shown that SAIC is able to achieve near-optimal performance in terms of the achieved sum of discounted rewards. The proposed algorithm is applied to a geometric consensus problem and its performance is compared with several benchmarks. Numerical experiments confirm the promise of this indirect design approach for task-oriented multi-agent communications.
AbstractList	Various applications for inter-machine communications are on the rise. Whether it is for autonomous driving vehicles or the Internet of everything, machines are more connected than ever to improve their performance in fulfilling a given task. While in traditional communications the goal has often been to reconstruct the underlying message, under the emerging task-oriented paradigm, the goal of communication is to enable the receiving end to make more informed decisions or more precise estimates/computations. Motivated by these recent developments, in this paper, we perform an indirect design of the communications in a multi-agent system (MAS) in which agents cooperate to maximize the averaged sum of discounted one-stage rewards of a collaborative task. Due to the bit-budgeted communications between the agents, each agent should efficiently represent its local observation and communicate an abstracted version of the observations to improve the collaborative task performance. We first show that this problem can be approximated as a form of data-quantization problem which we call task-oriented data compression (TODC). We then introduce the state-aggregation for information compression algorithm (SAIC) to solve the formulated TODC problem. It is shown that SAIC is able to achieve near-optimal performance in terms of the achieved sum of discounted rewards. The proposed algorithm is applied to a geometric consensus problem and its performance is compared with several benchmarks. Numerical experiments confirm the promise of this indirect design approach for task-oriented multi-agent communications.
Author	Mostaani, Arsham Ottersten, Bjorn Vu, Thang X. Chatzinotas, Symeon
Author_xml	– sequence: 1 givenname: Arsham orcidid: 0000-0001-9183-4411 surname: Mostaani fullname: Mostaani, Arsham organization: Centre for Security Reliability and Trust, University of Luxembourg, Luxembourg – sequence: 2 givenname: Thang X. orcidid: 0000-0002-8374-443X surname: Vu fullname: Vu, Thang X. organization: Centre for Security Reliability and Trust, University of Luxembourg, Luxembourg – sequence: 3 givenname: Symeon orcidid: 0000-0001-5122-0001 surname: Chatzinotas fullname: Chatzinotas, Symeon organization: Centre for Security Reliability and Trust, University of Luxembourg, Luxembourg – sequence: 4 givenname: Bjorn orcidid: 0000-0003-2298-6774 surname: Ottersten fullname: Ottersten, Bjorn organization: Centre for Security Reliability and Trust, University of Luxembourg, Luxembourg
BackLink	https://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-337555$$DView record from Swedish Publication Index (Kungliga Tekniska Högskolan)
BookMark	eNp9kU9P3DAQxa2KSoUtn4BLpJ6z9b848XEJ0FKBciituFleZ7x4ycaL7VD12zfZ0KrlUMmSrZn3fprxO0FHve8BoTOCl4Rg-bH5Uje3X5cUU7pklEznDTqmgvOc0OL-6K_3O3Qa4xZjTAtCCOPH6P5Ox8e8CQ76BG12oZPOar_bB4jR-T6zPmS3Q5dcvtqMkqm3G3pndBq7MWueIWTnLuXnQ7uBiVA_6L6HLr5Hb63uIpy-3Av07eryrv6c3zSfruvVTW44Fyln4xSCAa-qgpUt5pqvCSupqailYErDjeVUY0wMY6ay2jAhCo2rlpK2ao1mC3Q9c1uvt2of3E6Hn8prpw4FHzZKh-RMB0oSOToolWBLLnFZ6dYSvAbOJMGWmpGVz6z4A_bD-h_ahfu-OtAe04NirCyKYtR_mPX74J8GiElt_RD6cV1FS1oVQnIxqeSsMsHHGMAq49Lh_1LQrlMEqylHNeeophzVS46jl73y_p7p_66z2eUA4I9DSiIYFuwXL--qmA
CODEN	IOJCAZ
CitedBy_id	crossref_primary_10_1109_COMST_2024_3416309 crossref_primary_10_1109_ACCESS_2024_3360003 crossref_primary_10_1016_j_comnet_2025_111201 crossref_primary_10_1016_j_jfranklin_2024_106926 crossref_primary_10_1109_JIOT_2024_3354312 crossref_primary_10_1109_JSAC_2025_3574624 crossref_primary_10_1109_ACCESS_2022_3231039 crossref_primary_10_1109_JIOT_2023_3312553 crossref_primary_10_1109_TCOMM_2024_3416898 crossref_primary_10_1109_TCOMM_2024_3435131 crossref_primary_10_1109_TCOMM_2024_3365520
Cites_doi	10.1109/TIT.2018.2809008 10.1109/PIMRC.2019.8904190 10.1080/00207178808906054 10.3390/e23010104 10.4310/CIS.2020.v20.n2.a3 10.1109/ISIT50566.2022.9834593 10.1109/JSAC.2021.3087248 10.1007/978-3-319-28929-8 10.1016/j.artint.2010.09.008 10.1287/mnsc.28.1.1 10.1109/jsac.2022.3223408 10.1109/GLOBECOM42002.2020.9322138 10.1109/9.24227 10.1109/TIT.1982.1056489 10.1109/MSP.2020.2976000 10.1145/375735.376469 10.1613/jair.2447 10.1016/j.cogsys.2015.12.002 10.1016/j.comnet.2021.107930 10.1109/JSAC.2022.3191326 10.1109/TCDS.2018.2840971 10.1109/JAS.2018.7511249 10.1109/TSP.2018.2872832 10.1609/aaai.v32i1.11794 10.1109/GIIS48668.2019.9044966 10.1109/GIIS.2018.8635663 10.1613/jair.1024 10.1109/TCOM.1980.1094577 10.1109/TAC.2013.2293414 10.1609/icaps.v19i1.13355 10.1109/COMST.2022.3199901 10.1137/s0363012902402116 10.1109/TIT.1972.1054753 10.2307/3214403 10.1109/SMCIA.2008.5045926 10.1109/WINCOM.2018.8629632 10.1609/aaai.v34i04.5957 10.21236/ADA276517 10.1016/S0005-1098(02)00285-6 10.1109/TAC.2019.2912256 10.1109/TIT.1980.1056251
ContentType	Journal Article
Copyright	Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2022
Copyright_xml	– notice: Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2022
DBID	97E ESBDL RIA RIE AAYXX CITATION 7SP 8FD L7M ADTPV AFDQA AOWAS D8T D8V ZZAVC DOA
DOI	10.1109/OJCOMS.2022.3213213
DatabaseName	IEEE All-Society Periodicals Package (ASPP) 2005-present IEEE Open Access Journals IEEE All-Society Periodicals Package (ASPP) 1998-Present IEEE Electronic Library (IEL) CrossRef Electronics & Communications Abstracts Technology Research Database Advanced Technologies Database with Aerospace SwePub SWEPUB Kungliga Tekniska Högskolan full text SwePub Articles SWEPUB Freely available online SWEPUB Kungliga Tekniska Högskolan SwePub Articles full text DOAJ Directory of Open Access Journals
DatabaseTitle	CrossRef Technology Research Database Advanced Technologies Database with Aerospace Electronics & Communications Abstracts
DatabaseTitleList	Technology Research Database
Database_xml	– sequence: 1 dbid: DOA name: DOAJ Directory of Open Access Journals url: https://www.doaj.org/ sourceTypes: Open Website – sequence: 2 dbid: RIE name: IEEE Electronic Library (IEL) url: https://ieeexplore.ieee.org/ sourceTypes: Publisher
DeliveryMethod	fulltext_linktorsrc
Discipline	Engineering
EISSN	2644-125X
EndPage	1
ExternalDocumentID	oai_doaj_org_article_919dca229ef749078adf10be43910f2c oai_DiVA_org_kth_337555 10_1109_OJCOMS_2022_3213213 9916306
Genre	orig-research
GrantInformation_xml	– fundername: H2020 European Research Council grantid: ERC2020POC/957570/DREAM funderid: 10.13039/100010663
GroupedDBID	0R~ 97E AAJGR ABAZT ABVLG ALMA_UNASSIGNED_HOLDINGS BEFXN BFFAM BGNUA BKEBE BPEOZ EBS ESBDL GROUPED_DOAJ JAVBF M~E OCL OK1 RIA RIE AAYXX CITATION 7SP 8FD L7M ADTPV AFDQA AOWAS D8T D8V ZZAVC
ID	FETCH-LOGICAL-c446t-313463e488537d04a4b1372c82f2ec7c4cf42a001c33c8fac3665a08d21d8dca3
IEDL.DBID	DOA
ISICitedReferencesCount	12
ISICitedReferencesURI	http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000873729300004&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN	2644-125X
IngestDate	Fri Oct 03 12:43:13 EDT 2025 Tue Nov 04 16:30:31 EST 2025 Mon Jun 30 03:23:25 EDT 2025 Sat Nov 29 05:54:14 EST 2025 Tue Nov 18 21:59:14 EST 2025 Wed Aug 27 02:29:09 EDT 2025
IsDoiOpenAccess	true
IsOpenAccess	true
IsPeerReviewed	true
IsScholarly	true
Keywords	semantic communications data quantization Task-oriented communications machine learning for communications communications for machine learning
Language	English
License	https://creativecommons.org/licenses/by/4.0/legalcode
LinkModel	DirectLink
MergedId	FETCHMERGED-LOGICAL-c446t-313463e488537d04a4b1372c82f2ec7c4cf42a001c33c8fac3665a08d21d8dca3
Notes	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14
ORCID	0000-0003-2298-6774 0000-0001-5122-0001 0000-0001-9183-4411 0000-0002-8374-443X
OpenAccessLink	https://doaj.org/article/919dca229ef749078adf10be43910f2c
PQID	2728569465
PQPubID	5075783
PageCount	1
ParticipantIDs	crossref_citationtrail_10_1109_OJCOMS_2022_3213213 doaj_primary_oai_doaj_org_article_919dca229ef749078adf10be43910f2c crossref_primary_10_1109_OJCOMS_2022_3213213 ieee_primary_9916306 proquest_journals_2728569465 swepub_primary_oai_DiVA_org_kth_337555
PublicationCentury	2000
PublicationDate	20220000 2022-00-00 20220101 2022 2022-01-01
PublicationDateYYYYMMDD	2022-01-01
PublicationDate_xml	– year: 2022 text: 20220000
PublicationDecade	2020
PublicationPlace	New York
PublicationPlace_xml	– name: New York
PublicationTitle	IEEE open journal of the Communications Society
PublicationTitleAbbrev	OJCOMS
PublicationYear	2022
Publisher	IEEE The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher_xml	– name: IEEE – name: The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
References	ref13 ref12 ref15 ref53 ref52 ref11 ref55 ref10 Fischer (ref22) ref54 ref17 ref16 Sutton (ref45) 2017; 135 ref19 ref18 ref51 ref50 ref46 ref48 ref42 ref41 ref44 ref49 Kim (ref29) ref8 ref7 ref9 ref4 ref3 ref5 Foerster (ref26) ref40 Boutilier (ref47) 1999; 20 Lauer (ref14) ref34 Sukhbaatar (ref38) ref37 ref36 ref31 ref32 ref2 Zhang (ref21) ref39 Azar (ref56) Bertsekas (ref35) 2019 Mostaani (ref1) 2021 Lowe (ref30) ref24 ref23 ref25 Abel (ref33) ref20 Oliehoek (ref43) Barel (ref6) 2017 ref28 ref27
References_xml	– ident: ref44 doi: 10.1109/TIT.2018.2809008 – ident: ref27 doi: 10.1109/PIMRC.2019.8904190 – ident: ref5 doi: 10.1080/00207178808906054 – ident: ref18 doi: 10.3390/e23010104 – ident: ref8 doi: 10.4310/CIS.2020.v20.n2.a3 – year: 2021 ident: ref1 article-title: Task-oriented communication system design in cyberphysical systems: A survey on theory and applications publication-title: arXiv:2102.07166 – ident: ref39 doi: 10.1109/ISIT50566.2022.9834593 – ident: ref16 doi: 10.1109/JSAC.2021.3087248 – ident: ref50 doi: 10.1007/978-3-319-28929-8 – ident: ref24 doi: 10.1016/j.artint.2010.09.008 – ident: ref41 doi: 10.1287/mnsc.28.1.1 – ident: ref2 doi: 10.1109/jsac.2022.3223408 – ident: ref28 doi: 10.1109/GLOBECOM42002.2020.9322138 – ident: ref31 doi: 10.1109/9.24227 – ident: ref52 doi: 10.1109/TIT.1982.1056489 – start-page: 1334 volume-title: Proc. IEEE Joint Conf. Auton. Agents Multiagent Syst. (AAMAS) ident: ref22 article-title: Hierarchical reinforcement learning in communication-mediated multiagent coordination – ident: ref20 doi: 10.1109/MSP.2020.2976000 – start-page: 693 volume-title: Proc. Int. Conf. Auton. Agents MultiAgent Syst. ident: ref30 article-title: On the pitfalls of measuring emergent communication – ident: ref42 doi: 10.1145/375735.376469 – year: 2019 ident: ref35 article-title: Biased aggregation, Rollout, and enhanced policy improvement for reinforcement learning publication-title: arXiv:1910.02426 – start-page: 2244 volume-title: Proc. Adv. Neural Inf. Process. Syst. ident: ref38 article-title: Learning multiagent communication with backpropagation – ident: ref40 doi: 10.1613/jair.2447 – volume-title: Proc. Int. Conf. Learn. Represent. ident: ref29 article-title: Learning to schedule communication in multi-agent reinforcement learning – ident: ref49 doi: 10.1016/j.cogsys.2015.12.002 – ident: ref3 doi: 10.1016/j.comnet.2021.107930 – ident: ref7 doi: 10.1109/JSAC.2022.3191326 – volume: 135 volume-title: Introduction to Reinforcement Learning year: 2017 ident: ref45 – ident: ref46 doi: 10.1109/TCDS.2018.2840971 – ident: ref32 doi: 10.1109/JAS.2018.7511249 – ident: ref25 doi: 10.1109/TSP.2018.2872832 – start-page: 535 volume-title: Proc. Conf. Mach. Learn. ident: ref14 article-title: An algorithm for distributed reinforcement learning in cooperative multi-agent systems – start-page: 2915 volume-title: Proc. Int. Conf. Mach. Learn. ident: ref33 article-title: Near optimal behavior via approximate state abstraction – start-page: 1101 volume-title: Proc. Conf. Auton. Agents Multi-Agent Syst. ident: ref21 article-title: Coordinating multi-agent reinforcement learning with limited communication – ident: ref54 doi: 10.1609/aaai.v32i1.11794 – start-page: 2137 volume-title: Proc. Adv. Neural Inf. Process. Syst. ident: ref26 article-title: Learning to communicate with deep multi-agent reinforcement learning – ident: ref10 doi: 10.1109/GIIS48668.2019.9044966 – ident: ref9 doi: 10.1109/GIIS.2018.8635663 – ident: ref19 doi: 10.1613/jair.1024 – ident: ref53 doi: 10.1109/TCOM.1980.1094577 – volume-title: Proc. Multi-Agent Sequential Decis.-Making Uncertain Domains ident: ref43 article-title: DECPoMDPs with delayed communication – ident: ref51 doi: 10.1109/TAC.2013.2293414 – ident: ref55 doi: 10.1609/icaps.v19i1.13355 – year: 2017 ident: ref6 article-title: COME TOGETHER: Multi-agent geometric consensus publication-title: arXiv:1902.01455 – ident: ref11 doi: 10.1109/COMST.2022.3199901 – ident: ref13 doi: 10.1137/s0363012902402116 – ident: ref17 doi: 10.1109/TIT.1972.1054753 – ident: ref34 doi: 10.2307/3214403 – ident: ref23 doi: 10.1109/SMCIA.2008.5045926 – ident: ref36 doi: 10.1109/WINCOM.2018.8629632 – ident: ref37 doi: 10.1609/aaai.v34i04.5957 – ident: ref48 doi: 10.21236/ADA276517 – ident: ref12 doi: 10.1016/S0005-1098(02)00285-6 – ident: ref15 doi: 10.1109/TAC.2019.2912256 – ident: ref4 doi: 10.1109/TIT.1980.1056251 – volume: 20 start-page: 35 issue: 4 year: 1999 ident: ref47 article-title: Multiagent systems: Challenges and opportunities for decision-theoretic planning publication-title: AI Mag. – start-page: 2411 volume-title: Proc. NIPS ident: ref56 article-title: Speedy Q-learning
SSID	ssj0002511134
Score	2.2856774
Snippet	Various applications for inter-machine communications are on the rise. Whether it is for autonomous driving vehicles or the internet of everything, machines... Various applications for inter-machine communications are on the rise. Whether it is for autonomous driving vehicles or the Internet of everything, machines...
SourceID	doaj swepub proquest crossref ieee
SourceType	Open Website Open Access Repository Aggregation Database Enrichment Source Index Database Publisher
StartPage	1
SubjectTerms	Algorithms Collaboration Communication channels communications for machine learning Communications systems Data compression data quantization machine learning for communications Multi-agent systems Multiagent systems Quantization (signal) semantic communications Semantics Task analysis Task-oriented communications
SummonAdditionalLinks	– databaseName: IEEE Electronic Library (IEL) dbid: RIE link: http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1Lb9QwELZKxQEO5VEQKQXlgDg1rZ9xctxtqRASXSQK2pvljO2yKkpRN8vvx-O4UVdCSEg5RJFjO5mx5xvb8w0h7wTtKEjhKlBSRwclyKoVdaiYBSSMU8x1XUo2oS8umuWy_bJDjqZYGO99Onzmj_E27eW7G9jgUtkJYhmB_NoPtNZjrNa0noJQmQmZiYUYbU8Wn04Xn79GF5DzY8EZXlvGJ3H056Qq2_jyPmdosjPnT_6vh0_JXsaT5WxUgGdkx_fPyeN7LIP7ZHlp19fVAgmNI7wsz-xgS5wGxhOwfRlha5nicKsZxlmVWzEj63IRlb2cr4ZqvnFXHmvAiIQ-2tQX5Nv5h8vTj1VOqFBB9PqGON8KWQsfx6wS2lFpZceE5tDwwD1okBAkt9FwgRDQBAuirpWljePMNQ6seEl2-5vevyJl3fgIRDrbALUSeOiCYM4H60E60KErCL_70wYy2zgmvfhpktdBWzOKx6B4TBZPQY6ml36NZBv_Lj5HEU5FkSk7PYgiMXngmZa1seectz5o2UZAZF1gtPMYcUwDh4LsoxinSrIEC3J4pxAmj-q14Zo3qm5lrQryflSSrcbPVt9nqfHr4YcRQiulDv5e_WvyCL9kXMs5JLvD7ca_IQ_h97Ba375Nmv0HqLX3KA priority: 102 providerName: IEEE
Title	Task-Oriented Data Compression for Multi-Agent Communications Over Bit-Budgeted Channels
URI	https://ieeexplore.ieee.org/document/9916306 https://www.proquest.com/docview/2728569465 https://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-337555 https://doaj.org/article/919dca229ef749078adf10be43910f2c
Volume	3
WOSCitedRecordID	wos000873729300004&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
journalDatabaseRights	– providerCode: PRVAON databaseName: DOAJ Directory of Open Access Journals customDbUrl: eissn: 2644-125X dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0002511134 issn: 2644-125X databaseCode: DOA dateStart: 20200101 isFulltext: true titleUrlDefault: https://www.doaj.org/ providerName: Directory of Open Access Journals – providerCode: PRVHPJ databaseName: ROAD: Directory of Open Access Scholarly Resources (ISSN International Center) customDbUrl: eissn: 2644-125X dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0002511134 issn: 2644-125X databaseCode: M~E dateStart: 20200101 isFulltext: true titleUrlDefault: https://road.issn.org providerName: ISSN International Centre
link	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwrV1Lb9QwELZQxQEOCCiIQKl8QJwI9TN2jrt9CCG1i0RBe7OcsQ2rVgF1U478djxOutq9wAUpyiFybGdm7Pkm8nxDyBvJOgZKhhq0MjlASapuZZNq7gEJ4zQPXVeKTZiLC7tctp-2Sn3hmbCRHngU3FHL2wBeiDYmo3IkZ31InHURM0ZZEoC7b0Y9W8EU7sEInLlUE80QZ-3R4uPx4vxzDgiFeC8Fx2vHFRXG_qnEyi7a3GYQLV7n7DF5NMFFOhun-YTci_1T8nCLRHCfLC_9-qpeIF9xRo_0xA-e4iofD7j2NKNSWtJs6xmmUdGdlJA1XWRbpvPVUM9vw7eIPWDCQZ9d5jPy5ez08vhDPdVLqCEHdUPeTqVqZMxLUksTmPKq49IIsCKJCAYUJCV89ksgJdjkQTaN9swGwYPNQpbPyV7_o48vCG1szDij8xaYVyBSlyQPMfkIKoBJXUXEnegcTGTiWNPi2pWggrVulLdDebtJ3hV5t3np58il8ffmc9TJpikSYZcH2TzcZB7uX-ZRkX3U6KYThMM5SqrIwZ2G3bRo104YYXXTqkZX5O2o9Z3BT1ZfZ2Xwq-G7k9JorV_-jzm-Ig_wu8cfOwdkb7i5ja_Jffg1rNY3h8Ww8_389-lhSU_8Ay_m_FU
linkProvider	Directory of Open Access Journals
linkToHtml	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1Lb9QwEB5VBQk4lEepSCmQA-LUtPErj-NuS1Wg3UViQXuznLENq6It6mb5_XicNOpKCAkphyhybCcz9nxje74BeCvyJkcpbIZKlsFB8TKrReEzZpAI4xSzTROTTZSTSTWf15-34HCIhXHOxcNn7ohu416-vcY1LZUdE5YRxK99T0nJWRetNayoEFhmQvbUQiyvj6cfT6aXX4ITyPmR4IyuDfMTWfr7tCqbCPMua2i0NGeP_6-PT2CnR5TpqFOBp7Dlls_g0R2ewV2Yz8zqKpsSpXEAmOmpaU1KE0F3BnaZBuCaxkjcbESRVulG1MgqnQZ1T8eLNhuv7XdHNVBMwjJY1efw9ez97OQ861MqZBj8vjbMuEIWwoVRq0Rpc2lkw0TJseKeOyxRopfcBNOFQmDlDYqiUCavLGe2smjEHmwvr5fuBaRF5QIUaUyFuZHIfeMFs84bh9Ji6ZsE-O2f1tjzjVPai586-h15rTvxaBKP7sWTwOHw0q-ObuPfxcckwqEocWXHB0Ekuh96umZ16DnntfOlrAMkMtazvHEUc5x7jgnskhiHSnoJJnBwqxC6H9crzUteqaKWhUrgXackG42fLr6NYuNX7Q8tRKmU2v979W_gwfns8kJffJh8egkP6au6lZ0D2G5v1u4V3Mff7WJ18zpq-R-iiPpv
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%3Ajournal&rft.genre=article&rft.atitle=Task-Oriented+Data+Compression+for+Multi-Agent+Communications+Over+Bit-Budgeted+Channels&rft.jtitle=IEEE+open+journal+of+the+Communications+Society&rft.au=Mostaani%2C+Arsham&rft.au=Vu%2C+Thang+X.&rft.au=Chatzinotas%2C+Symeon&rft.au=Ottersten%2C+Bjorn&rft.date=2022&rft.issn=2644-125X&rft.eissn=2644-125X&rft.volume=3&rft.spage=1867&rft.epage=1886&rft_id=info:doi/10.1109%2FOJCOMS.2022.3213213&rft.externalDBID=n%2Fa&rft.externalDocID=10_1109_OJCOMS_2022_3213213
thumbnail_l	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=2644-125X&client=summon
thumbnail_m	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=2644-125X&client=summon
thumbnail_s	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=2644-125X&client=summon