Exploring the Impact of Coordination in Human–Agent Teams

2021 ◽  
pp. 155534342110105
Author(s):  
Michael Schneider ◽  
Michael Miller ◽  
David Jacques ◽  
Gilbert Peterson ◽  
Thomas Ford
Keyword(s):  
Artificial Agents ◽  
Effective Teams ◽  
Human Agent ◽  
Cognitive Work ◽  
Tightly Coupled ◽  
Agent Teams ◽  
The Impact ◽  
Critical Process

Teaming permits cognitively complex work to be rapidly executed by multiple entities. As artificial agents (AAs) participate in increasingly complex cognitive work, they hold the promise of moving beyond tools to becoming effective members of human–agent teams. Coordination has been identified as the critical process that enables effective teams and is required to achieve the vision of tightly coupled teams of humans and AAs. This paper characterizes coordination on the axes of types, content, and cost. This characterization is grounded in the human and AA literature and is evaluated to extract design implications for human–agent teams. These design implications are the mechanisms, moderators, and models employed within human–agent teams, which illuminate potential AA design improvements to support coordination.

Let's Think Together! Assessing Shared Mental Models, Performance, and Trust in Human-Agent Teams

2022 ◽  
Vol 6 (GROUP) ◽  
pp. 1-29
Author(s):  
Beau G. Schelble ◽  
Christopher Flathmann ◽  
Nathan J. McNeese ◽  
Guo Freeman ◽  
Rohit Mallick
Keyword(s):  
Mental Model ◽  
Cooperative Work ◽  
Computer Supported Cooperative Work ◽  
Team Composition ◽  
Team Cognition ◽  
Human Agent ◽  
Unique Nature ◽  
Agent Teams ◽  
Team Mental Model ◽  
The Impact

An emerging research agenda in Computer-Supported Cooperative Work focuses on human-agent teaming and AI agent's roles and effects in modern teamwork. In particular, one understudied key question centers around the construct of team cognition within human-agent teams. This study explores the unique nature of team dynamics in human-agent teams compared to human-human teams and the impact of team composition on perceived team cognition, team performance, and trust. In doing so, a mixed-method approach, including three team composition conditions (all human, human-human-agent, human-agent-agent), completed the team simulation NeoCITIES and completed shared mental model, trust, and perception measures. Results found that human-agent teams are similar to human-only teams in the iterative development of team cognition and the importance of communication to accelerating its development; however, human-agent teams are different in that action-related communication and explicitly shared goals are beneficial to developing team cognition. Additionally, human-agent teams trusted agent teammates less when working with only agents and no other humans, perceived less team cognition with agent teammates than human ones, and had significantly inconsistent levels of team mental model similarity when compared to human-only teams. This study contributes to Computer-Supported Cooperative Work in three significant ways: 1) advancing the existing research on human-agent teaming by shedding light on the relationship between humans and agents operating in collaborative environments, 2) characterizing team cognition development in human-agent teams; and 3) advancing real-world design recommendations that promote human-centered teaming agents and better integrate the two.

scholarly journals 3DIV update for 2021: a comprehensive resource of 3D genome and 3D cancer genome

2020 ◽  
Vol 49 (D1) ◽  
pp. D38-D46
Author(s):  
Kyukwang Kim ◽  
Insu Jang ◽  
Mooyoung Kim ◽  
Jinhyuk Choi ◽  
Min-Seo Kim ◽  
...  
Keyword(s):  
Cell Line ◽  
Large Scale ◽  
Three Dimensional ◽  
Cancer Cell Line ◽  
Cancer Genome ◽  
Structural Variations ◽  
3D Genome ◽  
Tightly Coupled ◽  
Regulatory Effects ◽  
The Impact

Abstract Three-dimensional (3D) genome organization is tightly coupled with gene regulation in various biological processes and diseases. In cancer, various types of large-scale genomic rearrangements can disrupt the 3D genome, leading to oncogenic gene expression. However, unraveling the pathogenicity of the 3D cancer genome remains a challenge since closer examinations have been greatly limited due to the lack of appropriate tools specialized for disorganized higher-order chromatin structure. Here, we updated a 3D-genome Interaction Viewer and database named 3DIV by uniformly processing ∼230 billion raw Hi-C reads to expand our contents to the 3D cancer genome. The updates of 3DIV are listed as follows: (i) the collection of 401 samples including 220 cancer cell line/tumor Hi-C data, 153 normal cell line/tissue Hi-C data, and 28 promoter capture Hi-C data, (ii) the live interactive manipulation of the 3D cancer genome to simulate the impact of structural variations and (iii) the reconstruction of Hi-C contact maps by user-defined chromosome order to investigate the 3D genome of the complex genomic rearrangement. In summary, the updated 3DIV will be the most comprehensive resource to explore the gene regulatory effects of both the normal and cancer 3D genome. ‘3DIV’ is freely available at http://3div.kr.

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 Hybrid Data Protection Framework to Enhance A2O Functionality in Production Database Virtualization

2020 ◽  
Vol 8 (6) ◽  
pp. 5691-5697
Keyword(s):  
Data Storage ◽  
Performance Indicator ◽  
Development Trend ◽  
Similar Data ◽  
Primary Role ◽  
City Development ◽  
Big Data Applications ◽  
Tightly Coupled ◽  
Deep Integration ◽  
The Impact

Deluge of information flows in the unprecedented scenario of smart city development trend, hence prone to issues on stability, reliability and availability. Smart data storage resources are vulnerable to provide functionality Always Available Online (A2O) due to their inherent heavy dependence on System Down Time (SDT), Redundant Systems and Software Failure (RS2F) or whole/ multiple site failures. In the absence of Production Database Management Services (PDMS), duplicate deployment of similar data on disjoint but similar architecture provides a Tightly Coupled Ultimate System (TCUS), which assures A2O mutually exclusive services. In this paper, we investigated active Data Guard (aDG) and Data Guard (DG) role management or switchover for a real time transition performed for database at standby state to cope up both planned maintenance and accidental RS2F events. We expose our results for deep integration of aDGs with ODB in-terms of Fast Sync to align synchronously at an ease of zero of wait states for disk I/O and configurability to Null Data Loss (NDL). Over a large range of remote or standby databases NDL make it certain to zero failover. The impact of aDG Fast-Start Failover in the cloud proximity make sure guaranteed NDL in synchronously and near NDL protection asynchronously. Hence, avoids unusual overhead impeding disk I/O and eventually on a primary database. We observe the key performance indicator in failover does not restart the standby database for primary role resumption, but introduce cloud proximity as a new primary database and the process is performed without any intervention of manual migration. The reliability of aDG Redo is flexible across not only standby databases but also primary sites running different operating system over diverse hardware platforms. The Redo capability enables migration with minimal downtime for any transaction in the clouds, therefore adds an inevitable functionality to big data applications.

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

The impact of cognitive work demands on subsequent physical activity behavior.

2022 ◽  
Author(s):  
Sven van As ◽  
Harm Veling ◽  
Debby G. J. Beckers ◽  
Fiona Earle ◽  
Stefi McMaster ◽  
...  
Keyword(s):  
Physical Activity ◽  
Physical Activity Behavior ◽  
Work Demands ◽  
Cognitive Work ◽  
Activity Behavior ◽  
The Impact

Agents and Social Interaction Insights from Social Psychology

2010 ◽  
pp. 74-91
Author(s):  
Joseph C. Bullington
Keyword(s):  
Social Psychology ◽  
Social Interaction ◽  
Social Perception ◽  
Attribution Theory ◽  
Interpersonal Relations ◽  
Human Interaction ◽  
Artificial Agents ◽  
Agent Based ◽  
Human Agent ◽  
Agent Interaction

Social interaction represents a powerful new locus of research in the quest to build more truly humanlike artificial agents. The work in this area, as in the field of human computer interaction, generally, is becoming more interdisciplinary in nature. In this spirit, the present chapter will survey concepts and theory from social psychology, a field many researchers may be unfamiliar with. Dennett’s notion of the intentional system will provide some initial grounding for the notion of social interaction, along with a brief discussion of conversational agents. The body of the chapter will then survey the areas of animal behavior and social psychology most relevant to human-agent interaction, concentrating on the areas of interpersonal relations and social perception. Within the area of social perception, the focus will be on the topics of emotion and attribution theory. Where relevant, research in the area of agent-human interaction will be discussed. The chapter will conclude with a brief survey of the use of agent-based modeling and simulation in social theory. The future looks very promising for researchers in this area; the complex problems involved in developing artificial agents who have mind-like attributes will require an interdisciplinary effort.

Systems modeling language extension to support modeling of human-agent teams

2020 ◽  
Author(s):  
Michael E. Miller ◽  
John M. McGuirl ◽  
Michael F. Schneider ◽  
Thomas C. Ford
Keyword(s):  
Modeling Language ◽  
Systems Modeling ◽  
Human Agent ◽  
Language Extension ◽  
Agent Teams
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