Developing an Interdisciplinary Language for Human-Agent Team Training Research

2005 ◽  
Vol 49 (25) ◽  
pp. 2149-2153 ◽  
Author(s):  
Stephen M. Fiore ◽  
Michael Rosen ◽  
Keith Garfield ◽  
Neal Finkelstein
Keyword(s):  
Computer Science ◽  
Intelligent Agents ◽  
Team Training ◽  
Human Agent ◽  
Training Research ◽  
Similarities And Differences ◽  
Agent Teams

In this paper we explore a set of constructs across three diverse disciplines that have addressed the topic of intelligent agents. We explore how Computer Science, Psychology, and Philosophy discuss certain concepts in either convergent or divergent ways. These concepts are analyzed through their etymology as well as by their present usage to illustrate how this use has developed and to outline the similarities and differences that have emerged. We first describe a set of the concepts/terms found within this literature and then describe the implications of this analysis for research in human-agent teams.

scholarly journals Human Theory of Mind Inference in Search and Rescue Tasks

2021 ◽  
Vol 65 (1) ◽  
pp. 648-652
Author(s):  
Huao Li ◽  
Keyang Zheng ◽  
Michael Lewis ◽  
Dana Hughes ◽  
Katia Sycara
Keyword(s):  
Experimental Study ◽  
Theory Of Mind ◽  
Social Interactions ◽  
Mental State ◽  
Intelligent Agents ◽  
Search And Rescue ◽  
Human Agent ◽  
Agent Teams

The ability to make inferences about other’s mental state is referred to as having a Theory of Mind (ToM). Such ability is the foundation of many human social interactions such as empathy, teamwork, and communication. As intelligent agents being involved in diverse human-agent teams, they are also expected to be socially intelligent to become effective teammates. To provide a feasible baseline for future social intelligent agents, this paper presents a experimental study on the process of human ToM reference. Human observers’ inferences are compared with participants’ verbally reported mental state in a simulated search and rescue task. Results show that ToM inference is a challenging task even for experienced human observers.

Developing an interdisciplinary language for human-agent team training research

2005 ◽  
Author(s):  
Stephen M. Fiore ◽  
Michael Rosen ◽  
Keith Garfield ◽  
Neal Finkelstein
Keyword(s):  
Team Training ◽  
Human Agent ◽  
Training Research

scholarly journals Trust repair in human-agent teams: the effectiveness of explanations and expressing regret

2021 ◽  
Vol 35 (2) ◽  
Author(s):  
E. S. Kox ◽  
J. H. Kerstholt ◽  
T. F. Hueting ◽  
P. W. de Vries
Keyword(s):  
Intelligent Agents ◽  
Intelligent Agent ◽  
Direct Interaction ◽  
Team Members ◽  
Trust Repair ◽  
Human Agent ◽  
Successful Team ◽  
Agent Teams ◽  
First Person Shooter

AbstractThe role of intelligent agents becomes more social as they are expected to act in direct interaction, involvement and/or interdependency with humans and other artificial entities, as in Human-Agent Teams (HAT). The highly interdependent and dynamic nature of teamwork demands correctly calibrated trust among team members. Trust violations are an inevitable aspect of the cycle of trust and since repairing damaged trust proves to be more difficult than building trust initially, effective trust repair strategies are needed to ensure durable and successful team performance. The aim of this study was to explore the effectiveness of different trust repair strategies from an intelligent agent by measuring the development of human trust and advice taking in a Human-Agent Teaming task. Data for this study were obtained using a task environment resembling a first-person shooter game. Participants carried out a mission in collaboration with their artificial team member. A trust violation was provoked when the agent failed to detect an approaching enemy. After this, the agent offered one of four trust repair strategies, composed of the apology components explanation and expression of regret (either one alone, both or neither). Our results indicated that expressing regret was crucial for effective trust repair. After trust declined due to the violation by the agent, trust only significantly recovered when an expression of regret was included in the apology. This effect was stronger when an explanation was added. In this context, the intelligent agent was the most effective in its attempt of rebuilding trust when it provided an apology that was both affective, and informational. Finally, the implications of our findings for the design and study of Human-Agent trust repair are discussed.

Team training research.

1965 ◽  
Author(s):  
George E. Briggs ◽  
William A. Johnston
Keyword(s):  
Team Training ◽  
Training Research

Autonomous Intelligent Agents for Team Training

2019 ◽  
Vol 34 (2) ◽  
pp. 3-14 ◽  
Author(s):  
Christopher Myers ◽  
Jerry Ball ◽  
Nancy Cooke ◽  
Mary Freiman ◽  
Michelle Caisse ◽  
...  
Keyword(s):  
Intelligent Agents ◽  
Team Training

scholarly journals The composition and formation of effective teams: computer science meets organizational psychology

2018 ◽  
Vol 33 ◽  
Author(s):  
Ewa Andrejczuk ◽  
Rita Berger ◽  
Juan A. Rodriguez-Aguilar ◽  
Carles Sierra ◽  
Víctor Marín-Puchades
Keyword(s):  
Computer Science ◽  
Team Performance ◽  
Organizational Psychology ◽  
Team Formation ◽  
Science Literature ◽  
Effective Teams ◽  
Human Agent ◽  
Wide Range ◽  
Psychology Literature ◽  
Cross Fertilization

AbstractNowadays the composition and formation of effective teams is highly important for both companies to assure their competitiveness and for a wide range of emerging applications exploiting multiagent collaboration (e.g. crowdsourcing, human-agent collaborations). The aim of this article is to provide an integrative perspective on team composition, team formation, and their relationship with team performance. Thus, we review the contributions in both the computer science literature and the organizational psychology literature dealing with these topics. Our purpose is twofold. First, we aim at identifying the strengths and weaknesses of the contributions made by these two diverse bodies of research. Second, we aim at identifying cross-fertilization opportunities that help both disciplines benefit from one another. Given the volume of existing literature, our review is not intended to be exhaustive. Instead, we have preferred to focus on the most significant contributions in both fields together with recent contributions that break new ground to spur innovative research.

Allocation of Moral Decision-Making in Human-Agent Teams: A Pattern Approach

2020 ◽  
pp. 203-220
Author(s):  
Jasper van der Waa ◽  
Jurriaan van Diggelen ◽  
Luciano Cavalcante Siebert ◽  
Mark Neerincx ◽  
Catholijn Jonker
Keyword(s):  
Decision Making ◽  
Moral Decision ◽  
Moral Decision Making ◽  
Human Agent ◽  
Pattern Approach ◽  
Agent Teams

scholarly journals The Attenuating Effect of Intelligent Agents and Agent Autonomy on Managers' Ability to Diffuse Responsibility for and Engage in Earnings Management

2020 ◽  
Vol 34 (4) ◽  
pp. 143-164
Author(s):  
Peter C. Kipp ◽  
Mary B. Curtis ◽  
Ziyin Li
Keyword(s):  
Earnings Management ◽  
Financial Reporting ◽  
Intelligent Agents ◽  
Autonomous Agents ◽  
Ethical Conduct ◽  
Human Agent ◽  
Perception Of Control ◽  
Reporting Decisions ◽  
Aggressive Financial Reporting

SYNOPSIS Advances in IT suggest that computerized intelligent agents (IAs) may soon occupy many roles that presently employ human agents. A significant concern is the ethical conduct of those who use IAs, including their possible utilization by managers to engage in earnings management. We investigate how financial reporting decisions are affected when they are supported by the work of an IA versus a human agent, with varying autonomy. In an experiment with experienced managers, we vary agent type (human versus IA) and autonomy (more versus less), finding that managers engage in less aggressive financial reporting decisions with IAs than with human agents, and engage in less aggressive reporting decisions with less autonomous agents than with more autonomous agents. Managers' perception of control over their agent and ability to diffuse their own responsibility for financial reporting decisions explain the effect of agent type and autonomy on managers' financial reporting decisions.

scholarly journals Individualized Mutual Adaptation in Human-Agent Teams

2021 ◽  
pp. 1-9
Author(s):  
Huao Li ◽  
Tianwei Ni ◽  
Siddharth Agrawal ◽  
Fan Jia ◽  
Suhas Raja ◽  
...  
Keyword(s):  
Human Agent ◽  
Mutual Adaptation ◽  
Agent Teams
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