دورية أكاديمية

JSwarm: A Jingulu-Inspired Human-AI-Teaming Language for Context-Aware Swarm Guidance

التفاصيل البيبلوغرافية
العنوان: JSwarm: A Jingulu-Inspired Human-AI-Teaming Language for Context-Aware Swarm Guidance
المؤلفون: Hussein A. Abbass, Eleni Petraki, Robert Hunjet
المصدر: Frontiers in Physics, Vol 10 (2022)
بيانات النشر: Frontiers Media S.A., 2022.
سنة النشر: 2022
المجموعة: LCC:Physics
مصطلحات موضوعية: human-AI teaming, human-swarm teaming, teaming languages, jingulu, human-swarm languages, Physics, QC1-999
الوصف: Bi-directional communication between humans and swarm systems begs for efficient languages to communicate information between the humans and the Artificial Intelligence (AI)-enabled agents in a manner that is most appropriate for the context. We discuss the criteria for effective teaming and functional bi-directional communication between humans and AI, and the design choices required to create effective languages. We then present a human-AI-teaming communication language inspired by the Australian Aboriginal language of Jingulu, which we call JSwarm. We present the motivation and structure of the language. An example is used to demonstrate how the language operates for a shepherding swarm guidance task.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 2296-424X
العلاقة: https://www.frontiersin.org/articles/10.3389/fphy.2022.944064/fullTest; https://doaj.org/toc/2296-424XTest
DOI: 10.3389/fphy.2022.944064
الوصول الحر: https://doaj.org/article/aeb2cd53956f473d97053a85531a5f4aTest
رقم الانضمام: edsdoj.b2cd53956f473d97053a85531a5f4a
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:2296424X
DOI:10.3389/fphy.2022.944064