Work

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

Year: 2022

Type: article

Abstract: 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.

Source: Frontiers in Physics

DOI: 10.3389/fphy.2022.944064

Authors: Hussein A. Abbass, Eleni Petraki, Robert Hunjet

Institutions: UNSW Canberra, University of Canberra, Defence Science and Technology Group

Language: English

Topic: Human-Automation Interaction and Safety

Subfield: Human Factors and Ergonomics

Field: Social Sciences

Domain: Social Sciences

Open Access status: gold

Estimated APC paid: $2,490

Funders: Office of Naval Research, Office of Naval Research Global