Introduction to Human Autonomy Teaming

Human-autonomy teaming (HAT) scenarios feature humans and autonomous agents collaborating to meet a shared goal.

The practical reality and feasibility of Human-Autonomy Teaming (HAT) are analyzed from an experts' point of view, considering current possibilities of various fields.

We combine machine education and communication theory as the two prerequisites for symbiosis of AI agents and present a formal computational model of symbiomemesis to enable symbiotic human-autonomy teaming.

ABSTRACT A Playbook delegation approach was evaluated for human-autonomy teaming (HAT) in Single Pilot Operations (SPO).

We believe that our naturally inspired human preferences with weakly supervised learning are beneficial for precise reward learning and can be applied to state-of-the-art RL systems, such as human-autonomy teaming systems.

Human-autonomy teaming is essential for future military operations, but guidance on how to design controls and displays to support joint decision-making and task completion is scarce.

A key challenge of safe and effective human-autonomy teaming is enabling “trust” between the human-machine team.

BACKGROUND Human-autonomy teaming presents challenges to teamwork, some of which may be addressed through training.

Increasingly autonomous systems, where autonomy is designed to support human-autonomy teaming, may be suited to solve these issues.

Human-autonomy teaming is a major emphasis in the ongoing transformation of future work space wherein human agents and autonomous agents are expected to work as a team.

The advancement of artificial situation awareness (ASA) technologies promotes intelligent agents to establish human-autonomy teaming (HAT) performing collaborative works with human as a teammate.

This paper argues that because of the cognitive and communication limitations of human and autonomous agents engaged in Human-Autonomy Teaming within dynamic environments, various external factors, which can be classified collectively as environment complexity, set boundaries to the effectiveness of strategies for agent transparency – that is, the ability of autonomous agents to make human actors aware of their goals, actions, reasoning, and expectations of future states.

The aim of this exploratory paper is to underline the importance of coordination-based training for dynamic tasks in human-autonomy teaming.

Human-Autonomy Teaming (HAT) is of growing interest in the military sector, particularly in its application to war gaming using semi-automated computer generated forces (CGF).

This paper presents preliminary results of an evaluation of a Playbook delegation interface for human-autonomy teaming (HAT) in Single Pilot Operations (SPO).