Interoperable AI: Evolutionary Race Towards Sustainable Knowledge Sharing - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Journal Articles IEEE Internet Computing Year : 2022

Interoperable AI: Evolutionary Race Towards Sustainable Knowledge Sharing

Abstract

The advancement and deployment of artificial intelligent agents brought numerous benefits in knowledge and data gathering and processing. However, one of the key challenges in deploying such agents in an open environment like the Web is their interoperability as they currently mostly run in silos. In this paper we report on a simulation and evaluation based on evolutionary agent-based modelling to empirically test how sustainable different strategies are for knowledge sharing in open multi-agent systems (MAS). Our results show the importance of translation-based approaches and the need for incentives to support these.
Fichier principal
Vignette du fichier
Sustainable web agents.pdf (2.87 Mo) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

hal-03807461 , version 1 (10-10-2022)
hal-03807461 , version 2 (11-10-2022)

Identifiers

Cite

Stefan Sarkadi, Andrea G. B. Tettamanzi, Fabien Gandon. Interoperable AI: Evolutionary Race Towards Sustainable Knowledge Sharing. IEEE Internet Computing, inPress, ⟨10.1109/MIC.2022.3214378⟩. ⟨hal-03807461v2⟩
64 View
43 Download

Altmetric

Share

Gmail Facebook Twitter LinkedIn More