Article (Périodiques scientifiques)
Task-Oriented Data Compression for Multi-Agent Communications Over Bit-Budgeted Channels
MOSTAANI, Arsham; VU, Thang Xuan; CHATZINOTAS, Symeon et al.
2022In IEEE Open Journal of the Communications Society
Peer reviewed vérifié par ORBi
 

Documents


Texte intégral
Task_Based_Quantization_for_Multi_Agent_Communication_Problems_Under_Bit_Budget___OJ_COMS___Final_Submission (4).pdf
Preprint Auteur (1.86 MB)
Télécharger
Annexes
Graphical Abstract - submission.pdf
(176.35 kB)
Télécharger

Tous les documents dans ORBilu sont protégés par une licence d'utilisation.

Envoyer vers



Détails



Mots-clés :
Task-oriented communications; semantic communications; data quantization
Résumé :
[en] 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.
Disciplines :
Ingénierie électrique & électronique
Auteur, co-auteur :
MOSTAANI, Arsham ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SigCom
VU, Thang Xuan  ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SigCom
CHATZINOTAS, Symeon  ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SigCom
OTTERSTEN, Björn  ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
Co-auteurs externes :
no
Langue du document :
Anglais
Titre :
Task-Oriented Data Compression for Multi-Agent Communications Over Bit-Budgeted Channels
Date de publication/diffusion :
06 octobre 2022
Titre du périodique :
IEEE Open Journal of the Communications Society
eISSN :
2644-125X
Maison d'édition :
Institute of Electrical and Electronics Engineers (IEEE), New York, Etats-Unis - New York
Peer reviewed :
Peer reviewed vérifié par ORBi
Focus Area :
Computational Sciences
Projet européen :
H2020 - 742648 - AGNOSTIC - Actively Enhanced Cognition based Framework for Design of Complex Systems
Intitulé du projet de recherche :
AGNOSTIC
Organisme subsidiant :
CER - Conseil Européen de la Recherche
CE - Commission Européenne
European Union
Disponible sur ORBilu :
depuis le 29 novembre 2022

Statistiques


Nombre de vues
207 (dont 10 Unilu)
Nombre de téléchargements
116 (dont 6 Unilu)

citations Scopus®
 
14
citations Scopus®
sans auto-citations
7
citations OpenAlex
 
13
citations WoS
 
12

Bibliographie


Publications similaires



Contacter ORBilu