Skip to Main Content (Press Enter)

Logo UNIRC
  • ×
  • Home
  • Corsi
  • Insegnamenti
  • Professioni
  • Persone
  • Pubblicazioni
  • Strutture
  • Attività
  • Competenze
  • Attrezzature

UNI-FIND
Logo UNIRC

|

UNI-FIND

unirc.it
  • ×
  • Home
  • Corsi
  • Insegnamenti
  • Professioni
  • Persone
  • Pubblicazioni
  • Strutture
  • Attività
  • Competenze
  • Attrezzature
  1. Pubblicazioni

Using local trust measures to form agent CoT groups1

Articolo
Data di Pubblicazione:
2020
Citazione:
Using local trust measures to form agent CoT groups1 / Fortino, G., Fotia, L., Messina, F., Rosaci, D., Sarne, G.M.L.. - In: INTELLIGENZA ARTIFICIALE. - ISSN 1724-8035. - 14:1(2020), pp. 77-88. [10.3233/IA-190039]
Abstract:
IoT devices dealing with complex tasks usually require powerful hardware capabilities or, as a possible alternative, to get on the Cloud those resources they need. When an IoT device is 'virtualized' on the Cloud, it can take benefit from relying on one or more software agents and their social skills to mutually interact and cooperate. In particular, in a Cloud of Things scenario, where agents cooperate to perform complex tasks, the choice of a partner is a sensitive question. In such a context, when an agent is not capable to perform a reliable choice then, like real social communities, it can ask information to other agents it considers as trustworthy. In order to support agents in their partner choices, we conceived a local trust model, based on reliability and reputation measures coming from its ego-network, adopted to partition the agents in groups by exploiting trust relationships to allow agents to be associated with the most reliable partners. To this aim, we designed an algorithm to form agent groups by exploiting available local trust measures and the results obtained in a simulated scenario confirmed the potential advantages of this approach.
Tipologia CRIS:
1.1 Articolo in rivista
Elenco autori:
Fortino, G.; Fotia, L.; Messina, F.; Rosaci, D.; Sarne, G. M. L.
Autori di Ateneo:
ROSACI Domenico
Link alla scheda completa:
https://iris.unirc.it/handle/20.500.12318/74274
Link al Full Text:
https://iris.unirc.it//retrieve/handle/20.500.12318/74274/93143/fortino_2020_ia_using_post.pdf
Pubblicato in:
INTELLIGENZA ARTIFICIALE
Journal
  • Dati Generali

Dati Generali

URL

https://content.iospress.com/articles/intelligenza-artificiale/ia190039
  • Utilizzo dei cookie

Realizzato con VIVO | Designed by Cineca | 26.10.0.0