The impact of expressing emotion within explainable AI in human-agent teamwork

With the increasing development of artificial intelligence (AI), there is a more significant opportunity for humans and agents to collaborate in teamwork. In Human-Agent Teamwork (HAT) settings, collaboration requires communication, and the agent displaying emotion can impact how human teammates communicate and work together with the agent. This...

Design Guidelines for Human-Agent Collaboration in a Painting Context: Authority, Autonomy, and Delegation

This project focuses on developing design guidelines for Human-Agent Collaboration around Authority, Autonomy, and Control in the outdoor painting context. While painting as an activity is something most of us have done and understand, working professionals have a sense of pride and skill in their motions that would be difficult to replace with...

Goal Ontology for Personalized Learning and Its Implementation in Child's Health Self-Management Support

Intelligent tutoring systems need a model of learning goals for the personalization of educational content, tailoring of the learning path, progress monitoring, and adaptive feedback. This article presents such a model and corresponding interaction designs for the coaches and learners (respectively, a monitor-and-control dashboard and mobile...

NavAware: Data-centric design of a user-aware navigation agent for blind mobility

With the rise of digital technologies including artificial intelligence, machine learning, and sensor technologies, all the products we use every day are increasingly becoming ‘intelligent’. Machines, objects, and tools are slowly evolving into robots, objects-with-intent (Rozendaal et al., 2019), and agents. At the same time, their capabilities...

Assessing the Changes in Human Trustworthiness as a Result of an Artificial Agent Directing the Human in Joint Activities

The number of collaborations between humans and artificial agents has risen steeply in recent years due to the rapid expansion of AI. Numerous studies in social sciences have already established that trust is a crucial factor in ensuring effective teamwork. While the dynamics of trust in human-human relationships or the effects of human...

The Impact of Tailoring Agent Explanations According to Human Performance on Human-AI Teamwork

Nowadays, artificial intelligence (AI) systems are embedded in many aspects of our lives more than ever before. Autonomous AI systems (agents) are aiding people in mundane daily tasks, even outperforming humans in several cases. However, agents still depend on humans in unexpected circumstances. Thus, the main goal of these agents has...

Get a Grip on Stress with Grippy!: A Field Study to Understand Human-Wearable Partnerships in Stress Management

Smart wearables are increasingly used to help people deal with stress. Still, a less explored area of research in this field concerns the partnerships that smart wearables can take on when engaging people in stress-coping activities. To facilitate further understanding of the human-wearable partnerships, we designed Grippy, a smart wearable...

Assessing artificial trust in human-agent teams: A conceptual model

As intelligent agents are becoming human's teammates, not only do humans need to trust intelligent agents, but an intelligent agent should also be able to form artificial trust, i.e. a belief regarding human's trustworthiness. We see artificial trust as the beliefs of competence and willingness, and we study which internal factors (krypta) of...

Great Chain of Agents: The Role of Metaphorical Representation of Agents in Conversational Crowdsourcing

Conversational agents are being widely adopted across several domains to serve a variety of purposes ranging from providing intelligent assistance to companionship. Recent literature has shown that users develop intuitive folk theories and a metaphorical understanding of conversational agents (CAs) due to the lack of a mental model of the...

Influence of shared information on predictability in human-agent teams

Understanding trust in human-agent teams is of utmost importance if we want to ensure an efficient and effective collaboration. It is well known that predictability is a core component of trust, however it is still unclear what kind of information an agent should share in order to be perceived as predictable. Here we show that in a simple world...

The Influence of Information Sharing on the Predictability of the Human to an Agent

Mutual predictability shows itself as a contributing factor to mutual trust and is known to improve the effectiveness in a human-agent teamwork setting. As team members communicate to coordinate the team through the task, the question arises as to what information the human should share to be predictable to an agent. To experiment with measuring...

Engagement in Human-Agent Interaction: An Overview

Engagement is a concept of the utmost importance in human-computer interaction, not only for informing the design and implementation of interfaces, but also for enabling more sophisticated interfaces capable of adapting to users. While the notion of engagement is actively being studied in a diverse set of domains, the term has been used to...

Facial feedback for reinforcement learning: a case study and offline analysis using the TAMER framework

Interactive reinforcement learning provides a way for agents to learn to solve tasks from evaluative feedback provided by a human user. Previous research showed that humans give copious feedback early in training but very sparsely thereafter. In this article, we investigate the potential of agent learning from trainers’ facial expressions via...

The Likeability-Success Tradeoff: Results of the 2^nd Annual Human-Agent Automated Negotiating Agents Competition

We present the results of the 2^nd Annual Human-Agent League of the Automated Negotiating Agent Competition. Building on the success of the previous year's results, a new challenge was issued that focused exploring the likeability-success tradeoff in negotiations. By examining a series of repeated negotiations, actions may affect...

Social interaction for efficient agent learning from human reward

Learning from rewards generated by a human trainer observing an agent in action has been proven to be a powerful method for teaching autonomous agents to perform challenging tasks, especially for those non-technical users. Since the efficacy of this approach depends critically on the reward the trainer provides, we consider how the...

Leveraging Social Networks to Motivate Humans to Train Agents (Extended Abstract)

Learning from rewards generated by a human trainer ob- serving the agent in action has been demonstrated to be an effective method for humans to teach an agent to perform challenging tasks. However, how to make the agent learn most efficiently from these kinds of human reward is still under-addressed. In this paper, we investigate the effect of...