Detailed Analysis of Team Movement and Communication Affecting Team Performance in the America's Army Game

Moon, Il‐Chul; Carley, Kathleen M.; Schneider, Mike; Shigiltchoff, Oleg

doi:10.21236/ada456149

Cited by 6 publications

(10 citation statements)

References 3 publications

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“…In fact, this actual-world constraint is in line with studies in the organisation psychology literature showing an inverse relationship between the size of a team and its performance[55,56,57,58] [56]. observes that in the case of a team containing more than six people there is a tendency to split the team into two, which brings about negative effects.…”

supporting

confidence: 75%

Synergistic team composition: A computational approach to foster diversity in teams

Andrejczuk

Bistaffa

Blum

et al. 2019

Knowledge-Based Systems

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Co-operative learning in heterogeneous teams refers to learning methods in which teams are organised both to accomplish academic tasks and for individuals to gain knowledge. Competencies, personality and the gender of team members are key factors that influence team performance. Here, we introduce a team composition problem, the so-called synergistic team composition problem (STCP), which incorporates such key factors when arranging teams. Thus, the goal of the STCP is to partition a set of individuals into a set of synergistic teams: teams that are diverse in personality and gender and whose members cover all required competencies to complete a task. Furthermore, the STCP requires that all teams are balanced in that they are expected to exhibit similar performances when completing the task. We propose two efficient algorithms to solve the STCP. Our first algorithm is based on a linear programming formulation and is appropriate to solve small instances of the problem. Our second algorithm is an anytime heuristic that is effective for large instances of the STCP. Finally, we thoroughly study the computational properties of both algorithms in an educational context when grouping students in a classroom into teams using actual-world data.

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supporting

confidence: 75%

Synergistic team composition: A computational approach to foster diversity in teams

Andrejczuk

Bistaffa

Blum

et al. 2019

Knowledge-Based Systems

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“…Similarly, in Moon et al . (2005) the plan is created by team members during a game. The domain used for this study is an on-line multi-player computer game called America’s Army, which is a first-person shooting game.…”

Section: Team Composition and Formation From A Computer Science Perspmentioning

confidence: 99%

“…(2013) validate their hypothesis by using virtual agents playing 691 instances of the GO computer game, and Moon et al . (2005) analyze the behaviour of approximately 150 000 teams in America’s Army game. Finally, Wax et al .…”

Section: Team Composition and Formation From A Computer Science Perspmentioning

confidence: 99%

“…A large part of the MAS literature focusses on the egalitarian setting, trying to benefit from leaderless teams that co-operate to complete tasks. We find this team structure in groupsourcing (Rokicki et al ., 2015), robust teams (Okimoto et al ., 2015; Crawford et al ., 2016), ad hoc teams (Chalkiadakis & Boutilier, 2012; Barrett et al ., 2013; Chen et al ., 2015), mixed teams (Hanna & Richards, 2015), learning teams (Liemhetcharat & Veloso, 2012, 2014) or online teams (Moon et al ., 2005).…”

Section: Team Composition and Formation From A Computer Science Perspmentioning

confidence: 99%

“…Furthermore, Moon et al . (2005) also highlight the importance of communication, as well as team movement structure on team performance. Regarding communication networks, two dominant communication network types are: star-shaped and long-chain shaped.…”

Section: Team Composition and Formation From A Computer Science Perspmentioning

confidence: 99%

See 2 more Smart Citations

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

Andrejczuk¹,

Berger

Rodŕıguez-Aguilar³

et al. 2018

The Knowledge Engineering Review

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Nowadays 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 organisational 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 pursue to identify cross-fertilisation 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.1. Capacity: individual and social capabilities of agents; and 2. Personality: individual behaviour models.

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Analyzing Team Decision-Making in Tactical Scenarios

Sukthankar

Sycara

2009

The Computer Journal

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Team decision-making is a bundle of interdependent activities that involve gathering, interpreting and exchanging information; creating and identifying alternative courses of action; choosing among alternatives by integrating the often different perspectives of team members and implementing a choice and monitoring its consequences. To accomplish joint tasks, human team members often assume distinctive roles in task completion. We believe that to design and build software agents that can assist human teams, we need develop automated techniques to identify the roles of the human decision-makers. If the supporting agents are insensitive to shifts in the team's roles, they cannot effectively monitor the team's activities. This article addresses the problem of doing offline role analysis of battle scenarios from multi-player team games. The ability to identify team roles from observations is important for a wide range of applications including automated commentary generation, game coaching and opponent modeling. We define a role as a preference model over possible actions based on the game state. This article explores two promising approaches for automated role analysis: (1) a model-based system for combining evidence from observed events using the Dempster-Shafer theory and (2) a data-driven discriminative classifier using support vector machines.

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Detailed Analysis of Team Movement and Communication Affecting Team Performance in the America's Army Game

Cited by 6 publications

References 3 publications

Synergistic team composition: A computational approach to foster diversity in teams

Synergistic team composition: A computational approach to foster diversity in teams

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

Analyzing Team Decision-Making in Tactical Scenarios

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