Ontology-Based Reflective Communication for Shared Human-AI Recognition of Emergent Collaboration Patterns

When humans and AI-agents collaborate, they need to continuously learn about each other and the task. We propose a Team Design Pattern that utilizes adaptivity in the behavior of human and agent team partners, causing new Collaboration Patterns to emerge. Human-AI Co-Learning takes place when partners can formalize recognized patterns of...

Trust Development in Military and Civilian Human–Agent Teams: The Effect of Social-Cognitive Recovery Strategies

Autonomous agents (AA) will increasingly be deployed as teammates instead of tools. In many operational situations, flawless performance from AA cannot be guaranteed. This may lead to a breach in the human’s trust, which can compromise collaboration. This highlights the importance of thinking about how to deal with error and trust violations...

The influence of interdependence and a transparent or explainable communication style on human-robot teamwork

Humans and robots are increasingly working together in human-robot teams. Teamwork requires communication, especially when interdependence between team members is high. In previous work, we identified a conceptual difference between sharing what you are doing (i.e., being transparent) and why you are doing it (i.e., being explainable). Although...

I’m Afraid I Can’t Do That, Dave: Getting to Know Your Buddies in a Human–Agent Team

The rapid progress in artificial intelligence enables technology to more and more become a partner of humans in a team, rather than being a tool. Even more than in human teams, partners of human–agent teams have different strengths and weaknesses, and they must acknowledge and utilize their respective capabilities. Coordinated team collaboration...

Trust Repair in Human-Agent Teams: the Effectiveness of Explanations and Expressing Regret

Trust is a fundamental aspect of teamwork in Human-Agent Teams (HATs). Trust violations are an inevitable aspect of the cycle of trust, so effective trust repair strategies are needed to ensure durable and successful team performance. This study explores the effectiveness of four trust repair strategies. In a first-person shooter resembling HAT...

Human-Robot Co-Learning for Fluent Collaborations

A team develops competency by progressive mutual adaptation and learning, a process we call co-learning. In human teams, partners naturally adapt to each other and learn while collaborating. This is not self-evident in human-robot teams. There is a need for methods and models for describing and enabling co-learning in human-robot partnerships....

A Two-Dimensional Explanation Framework to Classify AI as Incomprehensible, Interpretable, or Understandable

Because of recent and rapid developments in Artificial Intelligence (AI), humans and AI-systems increasingly work together in human-agent teams. However, in order to effectively leverage the capabilities of both, AI-systems need to be understandable to their human teammates. The branch of eXplainable AI (XAI) aspires to make AI-systems more...

Moral Decision Making in Human-Agent Teams: Human Control and the Role of Explanations

With the progress of Artificial Intelligence, intelligent agents are increasingly being deployed in tasks for which ethical guidelines and moral values apply. As artificial agents do not have a legal position, humans should be held accountable if actions do not comply, implying humans need to exercise control. This is often labeled as Meaningful...

Learning to communicate proactively in human-agent teaming

Artificially intelligent agents increasingly collaborate with humans in human-agent teams. Timely proactive sharing of relevant information within the team contributes to the overall team performance. This paper presents a machine learning approach to proactive communication in AI-agents using contextual factors. Proactive communication was...

Allocation of moral decision-making in human-agent teams: A pattern approach

Artificially intelligent agents will deal with more morally sensitive situations as the field of AI progresses. Research efforts are made to regulate, design and build Artificial Moral Agents (AMAs) capable of making moral decisions. This research is highly multidisciplinary with each their own jargon and vision, and so far it is unclear whether...

Team Design Patterns

This paper introduces the concept of team design patterns and proposes an intuitive graphical language for describing the design choices that influence how intelligent systems (e.g. artificial intelligence, robotics, etc.) collaborate with humans. We build on the notion of design patterns and characterize important dimensions within human-agent...

Developing Effective and Resilient Human-Agent Teamwork Using Team Design Patterns

Human-agent teams exhibit emergent behavior at the team level, as a result of interactions between individuals within the team. This begs the question how to design artificial team members (agents) as adequate team players that contribute to the team processes advancing team performance, resilience, and learning. This paper proposes the...

Six Challenges for Human-AI Co-learning

The increasing use of ever-smarter AI-technology is changing the way individuals and teams learn and perform their tasks. In hybrid teams, people collaborate with artificially intelligent partners. To utilize the different strengths and weaknesses of human and artificial intelligence, a hybrid team should be designed upon the principles that...

Explanation and coordination in human-agent teams: A study in the BW4T testbed

There are several applications in which humans and agents jointly perform a task. If the task involves interdependence among the team members, coordination is required to achieve good team performance. Coordination in human-agent teams can be improved by giving humans insight in the behavior of the agents. When humans are able to understand and...

Using artificial team members for team training in virtual environments

In a good team, members do not only perform their individual task, they also coordinate their actions with other members of the team. Developing such team skills usually involves exercises with all members playing their role. This approach is costly and has organizational and educational drawbacks. We developed a more efficient and flexible...

Implementing collective obligations in human-agent teams using KAoS policies

Obligations can apply to individuals, either severally or collectively. When applied severally, each individual or member of a team is independently responsible to fulfill the obligation. When applied collectively, it is the group as a whole that becomes responsible, with individual members sharing the obligation. In this paper, we present...

Assessing Human-Agent Teams for Future Space Missions

Running computer simulations of work practices early on lets researchers test humanagent teams in dangerous, complex environments by incrementally increasing fidelity, adding realistic features, and incorporating human participants.

Hybrid teams in virtual environments: Samurai joins the training team

This paper demonstrates a virtual environment where mixed human-agent teams are used for team-skills training. © Springer-Verlag 2009.